SFAM Final Project
Gen Shiraishi
2022-11-16
Overview
The objective of this exercise is to identify sustainability “top-performers” at the country level by comparing countries’ performance on sustainability indicators. This exercise relies primarily on the World Bank’s Sovereign Environmental, Social and Governance Data, which provides historical country-level data on 67 sustainability indicators. The World Bank’s ESG dataset is available here: https://datatopics.worldbank.org/esg/index.html. The version of the data used in this exercise was downloaded in October, 2022.
The methodology of this exercise is to rank-order countries based on
their performance on various sustainability indicators, such as
emissions and pollution levels, natural resource management and energy
use. Notably, countries will be assessed based on their performance
relative to other countries in their peer groups, in order to control
for capacity. As such, this exercise also utilizes a variety of IMF and
World Bank country groupings to enable peer-group comparisons.
# Data Preparation
Data preparation plan
The data preparation for this exercise involves cleaning and merging 2 datasets: the World Bank Sovereign ESG dataset and the IMF WB Country Groups dataset. The steps are as follows. Step 1: Load each dataset and review the data. Step 2: convert the country_name column in the IMF WB Country Groups dataset into iso3c codes. Step 3: Join the two datasets using the iso3c codes. The steps above will yield a combined dataset that includes ESG indicator data by country, with country groupings.
Load the data
folder_path <- partial(here, "00_data_raw")
folder_path() %>% list.files()## [1] "imf_wb_country_groups.csv"
## [2] "imf_wb_country_groups_exploration.xlsx"
## [3] "World Bank Sovereign ESG dataset"WB_sovereign_ESG <- folder_path("World Bank Sovereign ESG dataset/ESGData2.csv") %>%
read_csv()## Rows: 16013 Columns: 67
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): Country Name, iso3c, Indicator Name, Indicator Code
## dbl (63): 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, ...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.imf_wb_country_groups <- folder_path("imf_wb_country_groups.csv") %>%
read_csv()## Rows: 2587 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): country_name, country_group, group_type
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Review the WB ESG dataset and comment on its data structure
glimpse(WB_sovereign_ESG)## Rows: 16,013
## Columns: 67
## $ `Country Name` <chr> "Arab World", "Arab World", "Arab World", "Arab World…
## $ iso3c <chr> "ARB", "ARB", "ARB", "ARB", "ARB", "ARB", "ARB", "ARB…
## $ `Indicator Name` <chr> "Access to clean fuels and technologies for cooking (…
## $ `Indicator Code` <chr> "EG.CFT.ACCS.ZS", "EG.ELC.ACCS.ZS", "NY.ADJ.DRES.GN.Z…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, 30.981194, NA, NA, NA, NA, NA, NA, NA…
## $ `1962` <dbl> NA, NA, NA, NA, 30.982443, NA, NA, NA, NA, NA, NA, NA…
## $ `1963` <dbl> NA, NA, NA, NA, 31.006834, NA, NA, NA, NA, NA, NA, NA…
## $ `1964` <dbl> NA, NA, NA, NA, 31.01778, NA, NA, NA, NA, NA, NA, NA,…
## $ `1965` <dbl> NA, NA, NA, NA, 31.042245, NA, NA, NA, NA, NA, NA, NA…
## $ `1966` <dbl> NA, NA, NA, NA, 31.05018, NA, NA, NA, NA, NA, NA, NA,…
## $ `1967` <dbl> NA, NA, NA, NA, 31.103003, NA, NA, NA, NA, NA, NA, NA…
## $ `1968` <dbl> NA, NA, NA, NA, 31.133345, 14.660731, NA, NA, NA, NA,…
## $ `1969` <dbl> NA, NA, NA, NA, 31.190209, 14.295950, NA, NA, NA, NA,…
## $ `1970` <dbl> NA, NA, 6.8192031, 0.1745661, 31.2542726, 14.6376317,…
## $ `1971` <dbl> NA, NA, 6.8625877, 0.1392865, 31.3863673, 13.9126712,…
## $ `1972` <dbl> NA, NA, 8.9932942, 0.1320823, 31.4997277, 13.7760100,…
## $ `1973` <dbl> NA, NA, 12.2730219, 0.1524257, 31.4965877, 12.3616551…
## $ `1974` <dbl> NA, NA, 25.24123751, 0.08739206, 31.55058649, 7.77632…
## $ `1975` <dbl> NA, NA, 17.17663885, 0.09875801, 31.52950124, 7.98857…
## $ `1976` <dbl> NA, NA, 18.92687785, 0.06634076, 31.59973643, 7.44355…
## $ `1977` <dbl> NA, NA, 19.2409638, 0.1024133, 31.6219972, 7.1412275,…
## $ `1978` <dbl> NA, NA, 16.3069297, 0.1071046, 31.6660778, 7.1654123,…
## $ `1979` <dbl> NA, NA, 32.75748927, 0.07422815, 31.67849388, 5.67074…
## $ `1980` <dbl> NA, NA, 27.88409161, 0.05775981, 31.75886761, 4.75050…
## $ `1981` <dbl> NA, NA, 20.08867813, 0.05511109, 31.45424086, 5.07641…
## $ `1982` <dbl> NA, NA, 10.9940045, 0.1141440, 31.4801559, 5.9800629,…
## $ `1983` <dbl> NA, NA, 9.65310503, 0.08148845, 31.52860052, 6.738849…
## $ `1984` <dbl> NA, NA, 9.7577998, 0.0795408, 31.9421227, 7.3157059, …
## $ `1985` <dbl> NA, NA, 8.32055276, 0.03830571, 32.44202971, 8.068573…
## $ `1986` <dbl> NA, NA, 5.59763556, 0.08965615, 33.02639234, 9.621148…
## $ `1987` <dbl> NA, NA, 7.36173263, 0.08506867, 33.58285192, 10.27551…
## $ `1988` <dbl> NA, NA, 6.5508191, 0.0897014, 34.1868305, 10.5341524,…
## $ `1989` <dbl> NA, NA, 9.05466681, 0.08732953, 34.69763715, 11.08920…
## $ `1990` <dbl> NA, NA, 7.98566651, 0.06761466, 35.10930645, 10.38169…
## $ `1991` <dbl> NA, NA, 8.43729462, 0.07275225, 35.15972003, 12.27688…
## $ `1992` <dbl> NA, NA, 8.51357510, 0.05785795, 35.32097250, 9.225802…
## $ `1993` <dbl> NA, NA, 8.14964549, 0.04460087, 36.09585061, 9.263672…
## $ `1994` <dbl> NA, NA, 7.44516045, 0.04575975, 36.75422959, 10.22704…
## $ `1995` <dbl> NA, NA, 7.67706491, 0.06196782, 37.38644379, 10.38116…
## $ `1996` <dbl> NA, 76.61107378, 8.91043066, 0.05868878, 37.98259419,…
## $ `1997` <dbl> NA, 77.25362114, 7.75296001, 0.05524078, 38.49337516,…
## $ `1998` <dbl> NA, 78.11157597, 5.40270002, 0.07836069, 39.11826905,…
## $ `1999` <dbl> NA, 78.69106128, 7.00074834, 0.03706546, 39.64700699,…
## $ `2000` <dbl> 75.31875484, 80.73614121, 9.72850267, 0.02122214, 39.…
## $ `2001` <dbl> 76.65447960, 81.58623137, 7.51233649, 0.02455567, 39.…
## $ `2002` <dbl> 77.85548458, 81.54022203, 7.39429040, 0.02680793, 39.…
## $ `2003` <dbl> 79.04554536, 82.50815948, 8.71632561, 0.03261723, 39.…
## $ `2004` <dbl> 80.03416635, 82.50368475, 10.19516060, 0.02505279, 40…
## $ `2005` <dbl> 81.02576797, 83.21298163, 12.94744287, 0.02041118, 40…
## $ `2006` <dbl> 81.96581490, 85.45900327, 12.83170086, 0.02157661, 40…
## $ `2007` <dbl> 82.78718917, 83.76443999, 11.44096571, 0.01803353, 40…
## $ `2008` <dbl> 83.47573318, 83.38698965, 13.30778857, 0.02509408, 40…
## $ `2009` <dbl> 84.15742348, 84.31348380, 8.26486020, 0.02885193, 40.…
## $ `2010` <dbl> 84.68334427, 87.11486281, 9.45136425, 0.03003109, 40.…
## $ `2011` <dbl> 85.1927423, 87.3326612, 13.4275913, 0.0309041, 40.172…
## $ `2012` <dbl> 85.64421787, 87.03958839, 12.85922547, 0.03226624, 36…
## $ `2013` <dbl> 85.93256689, 88.99261981, 11.63839653, 0.06262475, 36…
## $ `2014` <dbl> 86.23238390, 88.01535618, 10.29789118, 0.08494782, 36…
## $ `2015` <dbl> 86.47859724, 88.68188567, 6.23770324, 0.09978365, 36.…
## $ `2016` <dbl> 86.72268517, 89.19506235, 5.20389537, 0.09505614, 36.…
## $ `2017` <dbl> 86.93793290, 90.32465949, 6.48008284, 0.09549819, 36.…
## $ `2018` <dbl> 87.04077373, 88.91074940, 8.47907008, 0.05105818, 36.…
## $ `2019` <dbl> 87.23553889, 89.99994555, 7.43714482, 0.06219453, 36.…
## $ `2020` <dbl> 87.30706752, 90.27773508, 4.37637424, 0.07908057, 36.…
## $ `2021` <dbl> NA, NA, NA, NA, NA, 5.237110, NA, NA, NA, NA, NA, NA,…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…The WB ESG dataset includes 67 columns and 16,013 rows.
The first 2 columns are the country name and the iso3c code. The next 2 columns are the indicator name and unique indicator code. Columns 5-66 include the value of the indicator for each year between 1960 and 2021. The final column 67 includes forecast values for 2050. Notably, many of the observations in columns 5-67 are blank, likely due to a lack of data.
Each row represents a unique combination of country and indicator, with the values of the indicator for the specific country included in columns 5-67. The Country Name and iso3c columns 1-2 include 239 unique countries and the indicator name and unique indicator code columns 3-4 include 67 unique indicators. The multiplication of these 239 countries and 67 indicators exactly yields the total 16,013 rows in the dataset.
Notably, multiple rows have blank values, likely due to data limitations, with some indicator rows for countries being entirely blank for each year column. Finally, the Country Name and iso3c columns include a subset of country groupings (e.g. “Arab World,” “Euro area”).
Review the IMF WB Country Groups dataset and comment on its data structure
glimpse(imf_wb_country_groups)## Rows: 2,587
## Columns: 3
## $ country_name <chr> "Australia", "Austria", "Belgium", "Canada", "Switzerlan…
## $ country_group <chr> "Advanced Economies", "Advanced Economies", "Advanced Ec…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", …The IMF WB Country Groups dataset includes 3 columns and 2,587 rows.
The columns are country name, country group (including various country groupings) and group type (an indication of whether the row is corresponds to an IMF or WB grouping).
Each row is a unique combination of a country name, country group and group type. The dataset includes 218 unique country names, 66 unique country groups and 2 unique group types (IMF or WB). 19 of the country groups are tagged as IMF and 48 are tagged as WB (“Euro Area” is the only country tagged as both IMF and WB and thus duplicated for each country).
Notably, each country has a different number of rows, depending on the number of country groupings that they fall under (e.g. Malawi has 15 rows as it falls under 15 country groupings while Australia has only 9 rows as it only falls under 9 country groupings). Finally, the IMF WB Country Groups dataset does not include iso3c country codes.
Convert country names to iso3c in the IMF WB Country Groups dataset
country_name_regex_to_iso3c <- function(country_name) {
country_name %>%
countrycode(origin = "country.name",
destination = "iso3c",
origin_regex = TRUE)
}
imf_wb_country_groups_iso3c <- imf_wb_country_groups %>%
mutate(iso3c = country_name_regex_to_iso3c(country_name))## Warning in countrycode_convert(sourcevar = sourcevar, origin = origin, destination = dest, : Some values were not matched unambiguously: Channel Islands, Kosovoimf_wb_country_groups_iso3c## # A tibble: 2,587 × 4
## country_name country_group group_type iso3c
## <chr> <chr> <chr> <chr>
## 1 Australia Advanced Economies IMF AUS
## 2 Austria Advanced Economies IMF AUT
## 3 Belgium Advanced Economies IMF BEL
## 4 Canada Advanced Economies IMF CAN
## 5 Switzerland Advanced Economies IMF CHE
## 6 Cyprus Advanced Economies IMF CYP
## 7 Czechia Advanced Economies IMF CZE
## 8 Germany Advanced Economies IMF DEU
## 9 Denmark Advanced Economies IMF DNK
## 10 Spain Advanced Economies IMF ESP
## # … with 2,577 more rowsMerge the two datasets using the iso3c country codes
The left join function, taking the WB ESG dataset as the “left” data frame, is most suitable in this case as this will add the country groups from the IMF WB Country Groups dataset to the WB ESG dataset as new columns, while preserving all rows in the ESG dataset (including the country groupings that are already included in the ESG dataset)
WB_sovereign_ESG_country_groups <- WB_sovereign_ESG %>% left_join(imf_wb_country_groups_iso3c, by = "iso3c")
glimpse(WB_sovereign_ESG_country_groups)## Rows: 169,175
## Columns: 70
## $ `Country Name` <chr> "Arab World", "Arab World", "Arab World", "Arab World…
## $ iso3c <chr> "ARB", "ARB", "ARB", "ARB", "ARB", "ARB", "ARB", "ARB…
## $ `Indicator Name` <chr> "Access to clean fuels and technologies for cooking (…
## $ `Indicator Code` <chr> "EG.CFT.ACCS.ZS", "EG.ELC.ACCS.ZS", "NY.ADJ.DRES.GN.Z…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, 30.981194, NA, NA, NA, NA, NA, NA, NA…
## $ `1962` <dbl> NA, NA, NA, NA, 30.982443, NA, NA, NA, NA, NA, NA, NA…
## $ `1963` <dbl> NA, NA, NA, NA, 31.006834, NA, NA, NA, NA, NA, NA, NA…
## $ `1964` <dbl> NA, NA, NA, NA, 31.01778, NA, NA, NA, NA, NA, NA, NA,…
## $ `1965` <dbl> NA, NA, NA, NA, 31.042245, NA, NA, NA, NA, NA, NA, NA…
## $ `1966` <dbl> NA, NA, NA, NA, 31.05018, NA, NA, NA, NA, NA, NA, NA,…
## $ `1967` <dbl> NA, NA, NA, NA, 31.103003, NA, NA, NA, NA, NA, NA, NA…
## $ `1968` <dbl> NA, NA, NA, NA, 31.133345, 14.660731, NA, NA, NA, NA,…
## $ `1969` <dbl> NA, NA, NA, NA, 31.190209, 14.295950, NA, NA, NA, NA,…
## $ `1970` <dbl> NA, NA, 6.8192031, 0.1745661, 31.2542726, 14.6376317,…
## $ `1971` <dbl> NA, NA, 6.8625877, 0.1392865, 31.3863673, 13.9126712,…
## $ `1972` <dbl> NA, NA, 8.9932942, 0.1320823, 31.4997277, 13.7760100,…
## $ `1973` <dbl> NA, NA, 12.2730219, 0.1524257, 31.4965877, 12.3616551…
## $ `1974` <dbl> NA, NA, 25.24123751, 0.08739206, 31.55058649, 7.77632…
## $ `1975` <dbl> NA, NA, 17.17663885, 0.09875801, 31.52950124, 7.98857…
## $ `1976` <dbl> NA, NA, 18.92687785, 0.06634076, 31.59973643, 7.44355…
## $ `1977` <dbl> NA, NA, 19.2409638, 0.1024133, 31.6219972, 7.1412275,…
## $ `1978` <dbl> NA, NA, 16.3069297, 0.1071046, 31.6660778, 7.1654123,…
## $ `1979` <dbl> NA, NA, 32.75748927, 0.07422815, 31.67849388, 5.67074…
## $ `1980` <dbl> NA, NA, 27.88409161, 0.05775981, 31.75886761, 4.75050…
## $ `1981` <dbl> NA, NA, 20.08867813, 0.05511109, 31.45424086, 5.07641…
## $ `1982` <dbl> NA, NA, 10.9940045, 0.1141440, 31.4801559, 5.9800629,…
## $ `1983` <dbl> NA, NA, 9.65310503, 0.08148845, 31.52860052, 6.738849…
## $ `1984` <dbl> NA, NA, 9.7577998, 0.0795408, 31.9421227, 7.3157059, …
## $ `1985` <dbl> NA, NA, 8.32055276, 0.03830571, 32.44202971, 8.068573…
## $ `1986` <dbl> NA, NA, 5.59763556, 0.08965615, 33.02639234, 9.621148…
## $ `1987` <dbl> NA, NA, 7.36173263, 0.08506867, 33.58285192, 10.27551…
## $ `1988` <dbl> NA, NA, 6.5508191, 0.0897014, 34.1868305, 10.5341524,…
## $ `1989` <dbl> NA, NA, 9.05466681, 0.08732953, 34.69763715, 11.08920…
## $ `1990` <dbl> NA, NA, 7.98566651, 0.06761466, 35.10930645, 10.38169…
## $ `1991` <dbl> NA, NA, 8.43729462, 0.07275225, 35.15972003, 12.27688…
## $ `1992` <dbl> NA, NA, 8.51357510, 0.05785795, 35.32097250, 9.225802…
## $ `1993` <dbl> NA, NA, 8.14964549, 0.04460087, 36.09585061, 9.263672…
## $ `1994` <dbl> NA, NA, 7.44516045, 0.04575975, 36.75422959, 10.22704…
## $ `1995` <dbl> NA, NA, 7.67706491, 0.06196782, 37.38644379, 10.38116…
## $ `1996` <dbl> NA, 76.61107378, 8.91043066, 0.05868878, 37.98259419,…
## $ `1997` <dbl> NA, 77.25362114, 7.75296001, 0.05524078, 38.49337516,…
## $ `1998` <dbl> NA, 78.11157597, 5.40270002, 0.07836069, 39.11826905,…
## $ `1999` <dbl> NA, 78.69106128, 7.00074834, 0.03706546, 39.64700699,…
## $ `2000` <dbl> 75.31875484, 80.73614121, 9.72850267, 0.02122214, 39.…
## $ `2001` <dbl> 76.65447960, 81.58623137, 7.51233649, 0.02455567, 39.…
## $ `2002` <dbl> 77.85548458, 81.54022203, 7.39429040, 0.02680793, 39.…
## $ `2003` <dbl> 79.04554536, 82.50815948, 8.71632561, 0.03261723, 39.…
## $ `2004` <dbl> 80.03416635, 82.50368475, 10.19516060, 0.02505279, 40…
## $ `2005` <dbl> 81.02576797, 83.21298163, 12.94744287, 0.02041118, 40…
## $ `2006` <dbl> 81.96581490, 85.45900327, 12.83170086, 0.02157661, 40…
## $ `2007` <dbl> 82.78718917, 83.76443999, 11.44096571, 0.01803353, 40…
## $ `2008` <dbl> 83.47573318, 83.38698965, 13.30778857, 0.02509408, 40…
## $ `2009` <dbl> 84.15742348, 84.31348380, 8.26486020, 0.02885193, 40.…
## $ `2010` <dbl> 84.68334427, 87.11486281, 9.45136425, 0.03003109, 40.…
## $ `2011` <dbl> 85.1927423, 87.3326612, 13.4275913, 0.0309041, 40.172…
## $ `2012` <dbl> 85.64421787, 87.03958839, 12.85922547, 0.03226624, 36…
## $ `2013` <dbl> 85.93256689, 88.99261981, 11.63839653, 0.06262475, 36…
## $ `2014` <dbl> 86.23238390, 88.01535618, 10.29789118, 0.08494782, 36…
## $ `2015` <dbl> 86.47859724, 88.68188567, 6.23770324, 0.09978365, 36.…
## $ `2016` <dbl> 86.72268517, 89.19506235, 5.20389537, 0.09505614, 36.…
## $ `2017` <dbl> 86.93793290, 90.32465949, 6.48008284, 0.09549819, 36.…
## $ `2018` <dbl> 87.04077373, 88.91074940, 8.47907008, 0.05105818, 36.…
## $ `2019` <dbl> 87.23553889, 89.99994555, 7.43714482, 0.06219453, 36.…
## $ `2020` <dbl> 87.30706752, 90.27773508, 4.37637424, 0.07908057, 36.…
## $ `2021` <dbl> NA, NA, NA, NA, NA, 5.237110, NA, NA, NA, NA, NA, NA,…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_group <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ group_type <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…The merged dataset has 70 columns and 169,175 rows.
The columns correspond to the 67 columns in the WB ESG dataset plus the 3 columns from the IMF WB Country Groupings dataset.
The total number of rows has increased substantially because each row now represents a unique combination of country name, indicator, country group and group type. In other words, the 67 rows for each country in the WB ESG dataset was duplicated by the number of country groups that the country falls into in the IMF WB Country Groupings dataset. As an example, Australia now has 603 rows in the merged dataset because each of its 67 rows in the WB ESG dataset was duplicated 9 times (67 * 9 = 603) to create separate rows for each of the 9 country groupings that Australia falls under in the IMF WB Country Groupings dataset.
In addition, 3082 of the rows in the merged dataset are blank for the new columns 68-70 because they correspond to one of 46 “country names” in the WB ESG dataset that are actually country groupings (e.g. “Arab World”). These observations are marked as “NA” in these columns because they did not match with any observations in the iso3c column in the IMF WB Country Groupings dataset.
Finally, the blank observations in the WB ESG dataset have now been populated with “NA” in the merged dataset.
Write merged dataset to .csv
write.csv(WB_sovereign_ESG_country_groups,"C:/Users/Gen Shiraishi/Desktop/Sustainable Finance - Application and Methods/Final project/03_data_processed\\WB_sovereign_ESG_country_groups.csv", row.names = FALSE)Data analysis
Ranks top 10 LIDCs by performance on various indicators. Uses latest data.
Emissions & Pollution: CO2 Emissions per Capita
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_CO2_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EN.ATM.CO2E.PC') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_CO2_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "CO2 emissions (metric tons per capita)", "CO2 emissi…
## $ `Indicator Code` <chr> "EN.ATM.CO2E.PC", "EN.ATM.CO2E.PC", "EN.ATM.CO2E.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.19174511, 0.11165825, 0.06628517, 0.15071562, 0.056…
## $ `1991` <dbl> 0.16768158, 0.10255767, 0.05243232, 0.24315564, 0.056…
## $ `1992` <dbl> 0.09595774, 0.10946096, 0.05251505, 0.22449839, 0.055…
## $ `1993` <dbl> 0.08472111, 0.11390962, 0.05251948, 0.24409020, 0.055…
## $ `1994` <dbl> 0.07554583, 0.12010181, 0.04900061, 0.26320490, 0.055…
## $ `1995` <dbl> 0.06846796, 0.14370070, 0.05079965, 0.29927295, 0.056…
## $ `1996` <dbl> 0.06258803, 0.14305151, 0.15916585, 0.36936420, 0.060…
## $ `1997` <dbl> 0.05682662, 0.15787209, 0.19740055, 0.34438195, 0.064…
## $ `1998` <dbl> 0.05269086, 0.15690869, 0.18700905, 0.35437242, 0.069…
## $ `1999` <dbl> 0.04015697, 0.16063628, 0.20107735, 0.34608902, 0.078…
## $ `2000` <dbl> 0.03657370, 0.16959394, 0.20681782, 0.35532153, 0.080…
## $ `2001` <dbl> 0.03378536, 0.19817246, 0.24587634, 0.38101991, 0.081…
## $ `2002` <dbl> 0.04557366, 0.20705313, 0.29881844, 0.38959457, 0.078…
## $ `2003` <dbl> 0.05151838, 0.21240196, 0.32444410, 0.41411823, 0.082…
## $ `2004` <dbl> 0.04165539, 0.22286880, 0.34193536, 0.45396980, 0.081…
## $ `2005` <dbl> 0.06041878, 0.23526364, 0.36330733, 0.49326081, 0.078…
## $ `2006` <dbl> 0.06658329, 0.25475240, 0.42230074, 0.48676307, 0.089…
## $ `2007` <dbl> 0.06531235, 0.26629679, 0.47310460, 0.48129491, 0.098…
## $ `2008` <dbl> 0.12841656, 0.28814139, 0.46223287, 0.44668716, 0.115…
## $ `2009` <dbl> 0.17186242, 0.30666481, 0.49414666, 0.47174748, 0.114…
## $ `2010` <dbl> 0.24361404, 0.34273999, 0.52504257, 0.58351399, 0.146…
## $ `2011` <dbl> 0.29650624, 0.36456659, 0.49150028, 0.85100610, 0.152…
## $ `2012` <dbl> 0.25929533, 0.38402517, 0.45635565, 0.91222407, 0.177…
## $ `2013` <dbl> 0.18562366, 0.39669703, 0.46778508, 0.94334976, 0.183…
## $ `2014` <dbl> 0.14623562, 0.41309269, 0.50452817, 0.97350263, 0.180…
## $ `2015` <dbl> 0.17289674, 0.46199743, 0.52099282, 1.05785939, 0.204…
## $ `2016` <dbl> 0.14978933, 0.47082757, 0.61993701, 1.26237605, 0.198…
## $ `2017` <dbl> 0.13169456, 0.49685185, 0.61475453, 1.30103027, 0.222…
## $ `2018` <dbl> 0.16329530, 0.51711301, 0.64605812, 1.39184189, 0.236…
## $ `2019` <dbl> 0.15982437, 0.55652945, 0.61858375, 1.37597721, 0.246…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_CO2_LIDC <- WB_sovereign_ESG_country_groups_CO2_LIDC[!(is.na(WB_sovereign_ESG_country_groups_CO2_LIDC$"2019") | WB_sovereign_ESG_country_groups_CO2_LIDC$"2019"==""), ]
glimpse(WB_sovereign_ESG_country_groups_CO2_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "CO2 emissions (metric tons per capita)", "CO2 emissi…
## $ `Indicator Code` <chr> "EN.ATM.CO2E.PC", "EN.ATM.CO2E.PC", "EN.ATM.CO2E.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.19174511, 0.11165825, 0.06628517, 0.15071562, 0.056…
## $ `1991` <dbl> 0.16768158, 0.10255767, 0.05243232, 0.24315564, 0.056…
## $ `1992` <dbl> 0.09595774, 0.10946096, 0.05251505, 0.22449839, 0.055…
## $ `1993` <dbl> 0.08472111, 0.11390962, 0.05251948, 0.24409020, 0.055…
## $ `1994` <dbl> 0.07554583, 0.12010181, 0.04900061, 0.26320490, 0.055…
## $ `1995` <dbl> 0.06846796, 0.14370070, 0.05079965, 0.29927295, 0.056…
## $ `1996` <dbl> 0.06258803, 0.14305151, 0.15916585, 0.36936420, 0.060…
## $ `1997` <dbl> 0.05682662, 0.15787209, 0.19740055, 0.34438195, 0.064…
## $ `1998` <dbl> 0.05269086, 0.15690869, 0.18700905, 0.35437242, 0.069…
## $ `1999` <dbl> 0.04015697, 0.16063628, 0.20107735, 0.34608902, 0.078…
## $ `2000` <dbl> 0.03657370, 0.16959394, 0.20681782, 0.35532153, 0.080…
## $ `2001` <dbl> 0.03378536, 0.19817246, 0.24587634, 0.38101991, 0.081…
## $ `2002` <dbl> 0.04557366, 0.20705313, 0.29881844, 0.38959457, 0.078…
## $ `2003` <dbl> 0.05151838, 0.21240196, 0.32444410, 0.41411823, 0.082…
## $ `2004` <dbl> 0.04165539, 0.22286880, 0.34193536, 0.45396980, 0.081…
## $ `2005` <dbl> 0.06041878, 0.23526364, 0.36330733, 0.49326081, 0.078…
## $ `2006` <dbl> 0.06658329, 0.25475240, 0.42230074, 0.48676307, 0.089…
## $ `2007` <dbl> 0.06531235, 0.26629679, 0.47310460, 0.48129491, 0.098…
## $ `2008` <dbl> 0.12841656, 0.28814139, 0.46223287, 0.44668716, 0.115…
## $ `2009` <dbl> 0.17186242, 0.30666481, 0.49414666, 0.47174748, 0.114…
## $ `2010` <dbl> 0.24361404, 0.34273999, 0.52504257, 0.58351399, 0.146…
## $ `2011` <dbl> 0.29650624, 0.36456659, 0.49150028, 0.85100610, 0.152…
## $ `2012` <dbl> 0.25929533, 0.38402517, 0.45635565, 0.91222407, 0.177…
## $ `2013` <dbl> 0.18562366, 0.39669703, 0.46778508, 0.94334976, 0.183…
## $ `2014` <dbl> 0.14623562, 0.41309269, 0.50452817, 0.97350263, 0.180…
## $ `2015` <dbl> 0.17289674, 0.46199743, 0.52099282, 1.05785939, 0.204…
## $ `2016` <dbl> 0.14978933, 0.47082757, 0.61993701, 1.26237605, 0.198…
## $ `2017` <dbl> 0.13169456, 0.49685185, 0.61475453, 1.30103027, 0.222…
## $ `2018` <dbl> 0.16329530, 0.51711301, 0.64605812, 1.39184189, 0.236…
## $ `2019` <dbl> 0.15982437, 0.55652945, 0.61858375, 1.37597721, 0.246…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_CO2_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_CO2_LIDC$'2019')
WB_sovereign_ESG_country_groups_CO2_LIDC## # A tibble: 59 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG CO2 em… EN.ATM… NA NA NA NA NA NA
## 2 Bangladesh BGD CO2 em… EN.ATM… NA NA NA NA NA NA
## 3 Benin BEN CO2 em… EN.ATM… NA NA NA NA NA NA
## 4 Bhutan BTN CO2 em… EN.ATM… NA NA NA NA NA NA
## 5 Burkina Faso BFA CO2 em… EN.ATM… NA NA NA NA NA NA
## 6 Burundi BDI CO2 em… EN.ATM… NA NA NA NA NA NA
## 7 Cambodia KHM CO2 em… EN.ATM… NA NA NA NA NA NA
## 8 Cameroon CMR CO2 em… EN.ATM… NA NA NA NA NA NA
## 9 Central Afri… CAF CO2 em… EN.ATM… NA NA NA NA NA NA
## 10 Chad TCD CO2 em… EN.ATM… NA NA NA NA NA NA
## # … with 49 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_CO2_LIDC_top10 <- WB_sovereign_ESG_country_groups_CO2_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_CO2_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "CO2 Emissions per Capita - Top 10 LIDCs",
subtitle = "CO2 Emissions per Capita, Metric Tons, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_CO2_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_CO2_LIDC %>%
filter(`Rank` > 49)
#Chart bottom 10
WB_sovereign_ESG_country_groups_CO2_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "CO2 Emissions per Capita - Bottom 10 LIDCs",
subtitle = "CO2 Emissions per Capita, Metric Tons, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
No NAs
xxx
Emissions & Pollution: Methane Emissions per Capita
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_Methane_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EN.ATM.METH.PC') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_Methane_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Methane emissions (metric tons of CO2 equivalent per…
## $ `Indicator Code` <chr> "EN.ATM.METH.PC", "EN.ATM.METH.PC", "EN.ATM.METH.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.5430093, 0.6422288, 0.4459184, 1.0550093, 0.7660850…
## $ `1991` <dbl> 0.5278586, 0.6284143, 0.4485876, 1.0661439, 0.7690535…
## $ `1992` <dbl> 0.4922149, 0.6221309, 0.4426268, 1.0102428, 0.7690562…
## $ `1993` <dbl> 0.4558502, 0.6116865, 0.4292109, 1.0139132, 0.7631532…
## $ `1994` <dbl> 0.4374630, 0.6073391, 0.4427555, 1.0152189, 0.7609572…
## $ `1995` <dbl> 0.43234200, 0.60206683, 0.39962393, 1.10356897, 0.763…
## $ `1996` <dbl> 0.45986293, 0.58691072, 0.44632075, 1.05268794, 0.741…
## $ `1997` <dbl> 0.48560926, 0.57914169, 0.44574318, 1.03314584, 0.749…
## $ `1998` <dbl> 0.50461628, 0.56462672, 0.45284011, 0.99224279, 0.733…
## $ `1999` <dbl> 0.53443466, 0.57017489, 0.42616393, 1.02096257, 0.714…
## $ `2000` <dbl> 0.46005872, 0.56510424, 0.44859076, 0.94752409, 0.743…
## $ `2001` <dbl> 0.3864490, 0.5572351, 0.3758799, 0.8448702, 0.7015729…
## $ `2002` <dbl> 0.45131197, 0.55828104, 0.40025222, 0.82788846, 0.708…
## $ `2003` <dbl> 0.44381814, 0.55715638, 0.37896133, 0.81230885, 0.849…
## $ `2004` <dbl> 0.42464238, 0.54830249, 0.36258050, 0.79836068, 0.850…
## $ `2005` <dbl> 0.41825388, 0.55403114, 0.39838527, 0.89403522, 0.849…
## $ `2006` <dbl> 0.4229552, 0.5571201, 0.3736205, 0.8670467, 0.8192825…
## $ `2007` <dbl> 0.42840470, 0.55747782, 0.37375264, 0.87234703, 0.814…
## $ `2008` <dbl> 0.46532966, 0.57150119, 0.35299873, 0.75936813, 0.817…
## $ `2009` <dbl> 0.47156513, 0.57474813, 0.35216335, 0.79607391, 0.821…
## $ `2010` <dbl> 0.5208064, 0.5799068, 0.3391579, 0.7877439, 0.8356183…
## $ `2011` <dbl> 0.5146525, 0.5780009, 0.3424647, 0.7788870, 0.8270159…
## $ `2012` <dbl> 0.5015824, 0.5761371, 0.3391832, 0.7554355, 0.8068189…
## $ `2013` <dbl> 0.4902448, 0.5760617, 0.3508388, 0.7603118, 0.8059608…
## $ `2014` <dbl> 0.4884509, 0.5743043, 0.3373242, 0.7092662, 0.7994983…
## $ `2015` <dbl> 0.4637701, 0.5748889, 0.3337758, 0.6731833, 0.7873835…
## $ `2016` <dbl> 0.4473896, 0.5690696, 0.3394017, 0.6651229, 0.8060559…
## $ `2017` <dbl> 0.4300736, 0.5788255, 0.3328802, 0.6706341, 0.7950718…
## $ `2018` <dbl> 0.4280112, 0.5704045, 0.3326067, 0.6362706, 0.7812079…
## $ `2019` <dbl> 0.4303166, 0.5682440, 0.3313236, 0.6159136, 0.7799666…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_Methane_LIDC <- WB_sovereign_ESG_country_groups_Methane_LIDC[!(is.na(WB_sovereign_ESG_country_groups_Methane_LIDC$"2019") | WB_sovereign_ESG_country_groups_Methane_LIDC$"2019"==""), ]
glimpse(WB_sovereign_ESG_country_groups_Methane_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Methane emissions (metric tons of CO2 equivalent per…
## $ `Indicator Code` <chr> "EN.ATM.METH.PC", "EN.ATM.METH.PC", "EN.ATM.METH.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.5430093, 0.6422288, 0.4459184, 1.0550093, 0.7660850…
## $ `1991` <dbl> 0.5278586, 0.6284143, 0.4485876, 1.0661439, 0.7690535…
## $ `1992` <dbl> 0.4922149, 0.6221309, 0.4426268, 1.0102428, 0.7690562…
## $ `1993` <dbl> 0.4558502, 0.6116865, 0.4292109, 1.0139132, 0.7631532…
## $ `1994` <dbl> 0.4374630, 0.6073391, 0.4427555, 1.0152189, 0.7609572…
## $ `1995` <dbl> 0.43234200, 0.60206683, 0.39962393, 1.10356897, 0.763…
## $ `1996` <dbl> 0.45986293, 0.58691072, 0.44632075, 1.05268794, 0.741…
## $ `1997` <dbl> 0.48560926, 0.57914169, 0.44574318, 1.03314584, 0.749…
## $ `1998` <dbl> 0.50461628, 0.56462672, 0.45284011, 0.99224279, 0.733…
## $ `1999` <dbl> 0.53443466, 0.57017489, 0.42616393, 1.02096257, 0.714…
## $ `2000` <dbl> 0.46005872, 0.56510424, 0.44859076, 0.94752409, 0.743…
## $ `2001` <dbl> 0.3864490, 0.5572351, 0.3758799, 0.8448702, 0.7015729…
## $ `2002` <dbl> 0.45131197, 0.55828104, 0.40025222, 0.82788846, 0.708…
## $ `2003` <dbl> 0.44381814, 0.55715638, 0.37896133, 0.81230885, 0.849…
## $ `2004` <dbl> 0.42464238, 0.54830249, 0.36258050, 0.79836068, 0.850…
## $ `2005` <dbl> 0.41825388, 0.55403114, 0.39838527, 0.89403522, 0.849…
## $ `2006` <dbl> 0.4229552, 0.5571201, 0.3736205, 0.8670467, 0.8192825…
## $ `2007` <dbl> 0.42840470, 0.55747782, 0.37375264, 0.87234703, 0.814…
## $ `2008` <dbl> 0.46532966, 0.57150119, 0.35299873, 0.75936813, 0.817…
## $ `2009` <dbl> 0.47156513, 0.57474813, 0.35216335, 0.79607391, 0.821…
## $ `2010` <dbl> 0.5208064, 0.5799068, 0.3391579, 0.7877439, 0.8356183…
## $ `2011` <dbl> 0.5146525, 0.5780009, 0.3424647, 0.7788870, 0.8270159…
## $ `2012` <dbl> 0.5015824, 0.5761371, 0.3391832, 0.7554355, 0.8068189…
## $ `2013` <dbl> 0.4902448, 0.5760617, 0.3508388, 0.7603118, 0.8059608…
## $ `2014` <dbl> 0.4884509, 0.5743043, 0.3373242, 0.7092662, 0.7994983…
## $ `2015` <dbl> 0.4637701, 0.5748889, 0.3337758, 0.6731833, 0.7873835…
## $ `2016` <dbl> 0.4473896, 0.5690696, 0.3394017, 0.6651229, 0.8060559…
## $ `2017` <dbl> 0.4300736, 0.5788255, 0.3328802, 0.6706341, 0.7950718…
## $ `2018` <dbl> 0.4280112, 0.5704045, 0.3326067, 0.6362706, 0.7812079…
## $ `2019` <dbl> 0.4303166, 0.5682440, 0.3313236, 0.6159136, 0.7799666…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_Methane_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_Methane_LIDC$'2019')
WB_sovereign_ESG_country_groups_Methane_LIDC## # A tibble: 59 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Methan… EN.ATM… NA NA NA NA NA NA
## 2 Bangladesh BGD Methan… EN.ATM… NA NA NA NA NA NA
## 3 Benin BEN Methan… EN.ATM… NA NA NA NA NA NA
## 4 Bhutan BTN Methan… EN.ATM… NA NA NA NA NA NA
## 5 Burkina Faso BFA Methan… EN.ATM… NA NA NA NA NA NA
## 6 Burundi BDI Methan… EN.ATM… NA NA NA NA NA NA
## 7 Cambodia KHM Methan… EN.ATM… NA NA NA NA NA NA
## 8 Cameroon CMR Methan… EN.ATM… NA NA NA NA NA NA
## 9 Central Afri… CAF Methan… EN.ATM… NA NA NA NA NA NA
## 10 Chad TCD Methan… EN.ATM… NA NA NA NA NA NA
## # … with 49 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_Methane_LIDC_top10 <- WB_sovereign_ESG_country_groups_Methane_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_Methane_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Methane Emissions per Capita - Top 10 LIDCs",
subtitle = "Methane Emissions per Capita, Metric Tons of CO2 Equivalent, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_Methane_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_Methane_LIDC %>%
filter(`Rank` > 49)
#Chart bottom 10
WB_sovereign_ESG_country_groups_Methane_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Methane Emissions per Capita - Bottom 10 LIDCs",
subtitle = "Methane Emissions per Capita, Metric Tons of CO2 Equivalent, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
No NAs
Emissions & Pollution: Nitrous Oxide Emissions per Capita
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_N2O_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EN.ATM.NOXE.PC') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_N2O_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Nitrous oxide emissions (metric tons of CO2 equivale…
## $ `Indicator Code` <chr> "EN.ATM.NOXE.PC", "EN.ATM.NOXE.PC", "EN.ATM.NOXE.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.2288051, 0.1592487, 0.3274086, 0.2072340, 0.5368270…
## $ `1991` <dbl> 0.22031705, 0.16306953, 0.32818746, 0.20574708, 0.545…
## $ `1992` <dbl> 0.19950926, 0.16233930, 0.32259244, 0.18708199, 0.542…
## $ `1993` <dbl> 0.18524840, 0.16239144, 0.31511686, 0.20653786, 0.535…
## $ `1994` <dbl> 0.16163293, 0.16471866, 0.32375401, 0.20680385, 0.548…
## $ `1995` <dbl> 0.15902235, 0.17235401, 0.30310460, 0.22445471, 0.545…
## $ `1996` <dbl> 0.16548701, 0.17322578, 0.34294498, 0.22161852, 0.525…
## $ `1997` <dbl> 0.17719573, 0.16569495, 0.34704291, 0.21750439, 0.534…
## $ `1998` <dbl> 0.18847114, 0.16261446, 0.35238070, 0.19490483, 0.526…
## $ `1999` <dbl> 0.19830600, 0.16926319, 0.33462873, 0.20765341, 0.523…
## $ `2000` <dbl> 0.16746907, 0.16732225, 0.34663832, 0.18612080, 0.550…
## $ `2001` <dbl> 0.14208364, 0.16788544, 0.27413799, 0.16566083, 0.490…
## $ `2002` <dbl> 0.1575167, 0.1692355, 0.3097842, 0.1785642, 0.5059750…
## $ `2003` <dbl> 0.15582197, 0.16291817, 0.26992685, 0.15927625, 0.595…
## $ `2004` <dbl> 0.14842262, 0.16132985, 0.25161281, 0.17219545, 0.593…
## $ `2005` <dbl> 0.14890306, 0.16456228, 0.29315142, 0.18497281, 0.598…
## $ `2006` <dbl> 0.13846298, 0.16966935, 0.26043907, 0.16732481, 0.567…
## $ `2007` <dbl> 0.13283867, 0.16823171, 0.26257305, 0.18048560, 0.560…
## $ `2008` <dbl> 0.13995962, 0.18079866, 0.23111644, 0.16378529, 0.554…
## $ `2009` <dbl> 0.1465057, 0.1753643, 0.2370115, 0.1621632, 0.5508187…
## $ `2010` <dbl> 0.15692718, 0.17719751, 0.23371460, 0.16046634, 0.558…
## $ `2011` <dbl> 0.1553918, 0.1822163, 0.2335948, 0.1586622, 0.5416022…
## $ `2012` <dbl> 0.15146955, 0.17615225, 0.23228914, 0.15678851, 0.530…
## $ `2013` <dbl> 0.14781718, 0.17517513, 0.23789071, 0.15487831, 0.531…
## $ `2014` <dbl> 0.15252854, 0.17913842, 0.23136359, 0.15297899, 0.520…
## $ `2015` <dbl> 0.13424924, 0.18149670, 0.22125647, 0.13738434, 0.510…
## $ `2016` <dbl> 0.14272379, 0.17356940, 0.23546570, 0.13573936, 0.522…
## $ `2017` <dbl> 0.14519462, 0.17897689, 0.22102528, 0.14753951, 0.510…
## $ `2018` <dbl> 0.12617050, 0.18174865, 0.24727831, 0.14581201, 0.501…
## $ `2019` <dbl> 0.13169739, 0.17737307, 0.23048599, 0.14415000, 0.497…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_N2O_LIDC <- WB_sovereign_ESG_country_groups_N2O_LIDC[!(is.na(WB_sovereign_ESG_country_groups_N2O_LIDC$"2019") | WB_sovereign_ESG_country_groups_N2O_LIDC$"2019"==""), ]
glimpse(WB_sovereign_ESG_country_groups_N2O_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Nitrous oxide emissions (metric tons of CO2 equivale…
## $ `Indicator Code` <chr> "EN.ATM.NOXE.PC", "EN.ATM.NOXE.PC", "EN.ATM.NOXE.PC",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 0.2288051, 0.1592487, 0.3274086, 0.2072340, 0.5368270…
## $ `1991` <dbl> 0.22031705, 0.16306953, 0.32818746, 0.20574708, 0.545…
## $ `1992` <dbl> 0.19950926, 0.16233930, 0.32259244, 0.18708199, 0.542…
## $ `1993` <dbl> 0.18524840, 0.16239144, 0.31511686, 0.20653786, 0.535…
## $ `1994` <dbl> 0.16163293, 0.16471866, 0.32375401, 0.20680385, 0.548…
## $ `1995` <dbl> 0.15902235, 0.17235401, 0.30310460, 0.22445471, 0.545…
## $ `1996` <dbl> 0.16548701, 0.17322578, 0.34294498, 0.22161852, 0.525…
## $ `1997` <dbl> 0.17719573, 0.16569495, 0.34704291, 0.21750439, 0.534…
## $ `1998` <dbl> 0.18847114, 0.16261446, 0.35238070, 0.19490483, 0.526…
## $ `1999` <dbl> 0.19830600, 0.16926319, 0.33462873, 0.20765341, 0.523…
## $ `2000` <dbl> 0.16746907, 0.16732225, 0.34663832, 0.18612080, 0.550…
## $ `2001` <dbl> 0.14208364, 0.16788544, 0.27413799, 0.16566083, 0.490…
## $ `2002` <dbl> 0.1575167, 0.1692355, 0.3097842, 0.1785642, 0.5059750…
## $ `2003` <dbl> 0.15582197, 0.16291817, 0.26992685, 0.15927625, 0.595…
## $ `2004` <dbl> 0.14842262, 0.16132985, 0.25161281, 0.17219545, 0.593…
## $ `2005` <dbl> 0.14890306, 0.16456228, 0.29315142, 0.18497281, 0.598…
## $ `2006` <dbl> 0.13846298, 0.16966935, 0.26043907, 0.16732481, 0.567…
## $ `2007` <dbl> 0.13283867, 0.16823171, 0.26257305, 0.18048560, 0.560…
## $ `2008` <dbl> 0.13995962, 0.18079866, 0.23111644, 0.16378529, 0.554…
## $ `2009` <dbl> 0.1465057, 0.1753643, 0.2370115, 0.1621632, 0.5508187…
## $ `2010` <dbl> 0.15692718, 0.17719751, 0.23371460, 0.16046634, 0.558…
## $ `2011` <dbl> 0.1553918, 0.1822163, 0.2335948, 0.1586622, 0.5416022…
## $ `2012` <dbl> 0.15146955, 0.17615225, 0.23228914, 0.15678851, 0.530…
## $ `2013` <dbl> 0.14781718, 0.17517513, 0.23789071, 0.15487831, 0.531…
## $ `2014` <dbl> 0.15252854, 0.17913842, 0.23136359, 0.15297899, 0.520…
## $ `2015` <dbl> 0.13424924, 0.18149670, 0.22125647, 0.13738434, 0.510…
## $ `2016` <dbl> 0.14272379, 0.17356940, 0.23546570, 0.13573936, 0.522…
## $ `2017` <dbl> 0.14519462, 0.17897689, 0.22102528, 0.14753951, 0.510…
## $ `2018` <dbl> 0.12617050, 0.18174865, 0.24727831, 0.14581201, 0.501…
## $ `2019` <dbl> 0.13169739, 0.17737307, 0.23048599, 0.14415000, 0.497…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_N2O_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_N2O_LIDC$'2019')
WB_sovereign_ESG_country_groups_N2O_LIDC## # A tibble: 59 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Nitrou… EN.ATM… NA NA NA NA NA NA
## 2 Bangladesh BGD Nitrou… EN.ATM… NA NA NA NA NA NA
## 3 Benin BEN Nitrou… EN.ATM… NA NA NA NA NA NA
## 4 Bhutan BTN Nitrou… EN.ATM… NA NA NA NA NA NA
## 5 Burkina Faso BFA Nitrou… EN.ATM… NA NA NA NA NA NA
## 6 Burundi BDI Nitrou… EN.ATM… NA NA NA NA NA NA
## 7 Cambodia KHM Nitrou… EN.ATM… NA NA NA NA NA NA
## 8 Cameroon CMR Nitrou… EN.ATM… NA NA NA NA NA NA
## 9 Central Afri… CAF Nitrou… EN.ATM… NA NA NA NA NA NA
## 10 Chad TCD Nitrou… EN.ATM… NA NA NA NA NA NA
## # … with 49 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_N2O_LIDC_top10 <- WB_sovereign_ESG_country_groups_N2O_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_N2O_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Nitrous Oxide Emissions per Capita - Top 10 LIDCs",
subtitle = "Nitrous Oxide Emissions per Capita, Metric Tons of CO2 Equivalent, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_N2O_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_N2O_LIDC %>%
filter(`Rank` > 49)
#Chart bottom 10
WB_sovereign_ESG_country_groups_N2O_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Nitrous Oxide Emissions per Capita - Bottom 10 LIDCs",
subtitle = "Nitrous Oxide Emissions per Capita, Metric Tons of CO2 Equivalent, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
Natural Resource Management: Natural Resources Depletion
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_NRD_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'NY.ADJ.DRES.GN.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_NRD_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Adjusted savings: natural resources depletion (% of …
## $ `Indicator Code` <chr> "NY.ADJ.DRES.GN.ZS", "NY.ADJ.DRES.GN.ZS", "NY.ADJ.DRE…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> 0.285942, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `1971` <dbl> 0.3489012, NA, 5.8471656, NA, NA, NA, NA, 3.8126547, …
## $ `1972` <dbl> 0.4044896, NA, 5.3683169, NA, NA, NA, NA, 3.7030249, …
## $ `1973` <dbl> 0.8008260, 0.4915004, 7.2654359, NA, NA, NA, NA, 4.84…
## $ `1974` <dbl> 0.9584073, 0.3739375, 7.2703839, NA, NA, NA, NA, 5.13…
## $ `1975` <dbl> 1.234269, 0.555508, 8.263988, NA, NA, NA, NA, 4.66532…
## $ `1976` <dbl> 1.3907038, 0.6723388, 7.1706735, NA, NA, NA, NA, 4.85…
## $ `1977` <dbl> 1.286721, 2.442155, 11.978642, NA, NA, NA, NA, 7.0161…
## $ `1978` <dbl> 1.228503, 1.758020, 9.871873, NA, NA, NA, NA, 5.35608…
## $ `1979` <dbl> 1.5692747, 0.6387094, 7.1601077, NA, NA, NA, NA, 8.05…
## $ `1980` <dbl> 1.65708765, 0.67651685, 7.32688047, 17.73298324, 0.00…
## $ `1981` <dbl> 1.276950388, 0.523311820, 7.339551751, 14.891426740, …
## $ `1982` <dbl> NA, 0.85321483, 10.15913167, 22.47814448, 0.00000000,…
## $ `1983` <dbl> NA, 0.59954798, 8.16483582, 14.79784479, 0.00000000, …
## $ `1984` <dbl> NA, 0.49725384, 9.16055585, 10.81186814, 0.06246862, …
## $ `1985` <dbl> NA, 0.30375768, 7.52682521, 7.40283960, 0.10435357, 6…
## $ `1986` <dbl> NA, 0.53163768, 7.41896468, 10.29386419, 0.18472956, …
## $ `1987` <dbl> NA, 0.43994382, 6.65457326, 6.96983113, 0.17981601, 9…
## $ `1988` <dbl> NA, 0.44166090, 6.46820754, 6.27951239, 0.17806530, 1…
## $ `1989` <dbl> NA, 0.40194032, 7.35355671, 5.97997299, 0.09617279, 1…
## $ `1990` <dbl> NA, 0.44926131, 7.00317073, 6.60248337, 0.05261745, 1…
## $ `1991` <dbl> NA, 0.44869537, 6.69571977, 8.20642308, 0.15899305, 1…
## $ `1992` <dbl> NA, 0.459461995, 9.020507879, 8.668348304, 0.01097204…
## $ `1993` <dbl> NA, 0.372735390, 5.636218344, 7.072893879, 0.00000000…
## $ `1994` <dbl> NA, 0.34039188, 9.11628246, 5.57452648, 0.09786290, 1…
## $ `1995` <dbl> NA, 0.387166446, 9.158089222, 6.671638748, 0.06052861…
## $ `1996` <dbl> NA, 0.35209206, 8.27020290, 6.30669083, 0.09401189, 2…
## $ `1997` <dbl> NA, 0.30112925, 7.89766951, 4.51414191, 0.07622930, 2…
## $ `1998` <dbl> NA, 0.285003352, 7.500319731, 4.796488637, 0.05450754…
## $ `1999` <dbl> NA, 0.317724562, 3.216121990, 5.085892944, 0.02344117…
## $ `2000` <dbl> NA, 0.391394931, 3.347154483, 3.874847322, 0.02809417…
## $ `2001` <dbl> NA, 0.423255055, 1.764083048, 3.616764917, 0.00920239…
## $ `2002` <dbl> NA, 0.504158418, 0.526683881, 3.442783032, 0.02744460…
## $ `2003` <dbl> NA, 0.471376666, 0.014839347, 3.265931367, 0.00787698…
## $ `2004` <dbl> NA, 0.489006624, 0.000282870, 2.898660515, 0.01810973…
## $ `2005` <dbl> NA, 0.608695844, 0.000428011, 2.446920110, 0.03219485…
## $ `2006` <dbl> NA, 0.885421294, 0.001336931, 3.113633345, 0.09394937…
## $ `2007` <dbl> NA, 0.845182140, 0.001031366, 3.997329793, 0.00014751…
## $ `2008` <dbl> NA, 0.775485842, 0.001132413, 3.590784153, 0.31868380…
## $ `2009` <dbl> 0.265019028, 0.804729858, 0.001390535, 3.344222964, 1…
## $ `2010` <dbl> 0.354491193, 0.848277731, 0.001917839, 4.934621990, 3…
## $ `2011` <dbl> 0.397696521, 1.184875777, 0.002939034, 4.552379054, 5…
## $ `2012` <dbl> 0.386703580, 1.231384811, 0.002668126, 3.969690083, 4…
## $ `2013` <dbl> 0.289482199, 0.902213141, 0.001599583, 3.228200928, 2…
## $ `2014` <dbl> 0.288231475, 0.893874568, 0.001230009, 3.257500653, 2…
## $ `2015` <dbl> 0.29524234, 0.77247401, 0.03924884, 3.83803073, 1.958…
## $ `2016` <dbl> 0.35595122, 0.50149103, 0.03795196, 4.31823948, 2.923…
## $ `2017` <dbl> 0.344837071, 0.483708671, 0.068336179, 3.264792706, 3…
## $ `2018` <dbl> 0.397920793, 0.518595806, 0.092259860, 1.907963892, 3…
## $ `2019` <dbl> 0.362219986, 0.359684399, 0.082064658, 2.072428649, 2…
## $ `2020` <dbl> 0.381654456, 0.278951688, 0.038834747, 2.654465117, 3…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_NRD_LIDC <- WB_sovereign_ESG_country_groups_NRD_LIDC[!(is.na(WB_sovereign_ESG_country_groups_NRD_LIDC$"2020") | WB_sovereign_ESG_country_groups_NRD_LIDC$"2020"==""), ]
glimpse(WB_sovereign_ESG_country_groups_NRD_LIDC)## Rows: 56
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Adjusted savings: natural resources depletion (% of …
## $ `Indicator Code` <chr> "NY.ADJ.DRES.GN.ZS", "NY.ADJ.DRES.GN.ZS", "NY.ADJ.DRE…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> 0.285942, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `1971` <dbl> 0.3489012, NA, 5.8471656, NA, NA, NA, NA, 3.8126547, …
## $ `1972` <dbl> 0.4044896, NA, 5.3683169, NA, NA, NA, NA, 3.7030249, …
## $ `1973` <dbl> 0.8008260, 0.4915004, 7.2654359, NA, NA, NA, NA, 4.84…
## $ `1974` <dbl> 0.9584073, 0.3739375, 7.2703839, NA, NA, NA, NA, 5.13…
## $ `1975` <dbl> 1.234269, 0.555508, 8.263988, NA, NA, NA, NA, 4.66532…
## $ `1976` <dbl> 1.3907038, 0.6723388, 7.1706735, NA, NA, NA, NA, 4.85…
## $ `1977` <dbl> 1.286721, 2.442155, 11.978642, NA, NA, NA, NA, 7.0161…
## $ `1978` <dbl> 1.228503, 1.758020, 9.871873, NA, NA, NA, NA, 5.35608…
## $ `1979` <dbl> 1.5692747, 0.6387094, 7.1601077, NA, NA, NA, NA, 8.05…
## $ `1980` <dbl> 1.65708765, 0.67651685, 7.32688047, 17.73298324, 0.00…
## $ `1981` <dbl> 1.276950388, 0.523311820, 7.339551751, 14.891426740, …
## $ `1982` <dbl> NA, 0.85321483, 10.15913167, 22.47814448, 0.00000000,…
## $ `1983` <dbl> NA, 0.59954798, 8.16483582, 14.79784479, 0.00000000, …
## $ `1984` <dbl> NA, 0.49725384, 9.16055585, 10.81186814, 0.06246862, …
## $ `1985` <dbl> NA, 0.30375768, 7.52682521, 7.40283960, 0.10435357, 6…
## $ `1986` <dbl> NA, 0.53163768, 7.41896468, 10.29386419, 0.18472956, …
## $ `1987` <dbl> NA, 0.43994382, 6.65457326, 6.96983113, 0.17981601, 9…
## $ `1988` <dbl> NA, 0.44166090, 6.46820754, 6.27951239, 0.17806530, 1…
## $ `1989` <dbl> NA, 0.40194032, 7.35355671, 5.97997299, 0.09617279, 1…
## $ `1990` <dbl> NA, 0.44926131, 7.00317073, 6.60248337, 0.05261745, 1…
## $ `1991` <dbl> NA, 0.44869537, 6.69571977, 8.20642308, 0.15899305, 1…
## $ `1992` <dbl> NA, 0.459461995, 9.020507879, 8.668348304, 0.01097204…
## $ `1993` <dbl> NA, 0.372735390, 5.636218344, 7.072893879, 0.00000000…
## $ `1994` <dbl> NA, 0.34039188, 9.11628246, 5.57452648, 0.09786290, 1…
## $ `1995` <dbl> NA, 0.387166446, 9.158089222, 6.671638748, 0.06052861…
## $ `1996` <dbl> NA, 0.35209206, 8.27020290, 6.30669083, 0.09401189, 2…
## $ `1997` <dbl> NA, 0.30112925, 7.89766951, 4.51414191, 0.07622930, 2…
## $ `1998` <dbl> NA, 0.285003352, 7.500319731, 4.796488637, 0.05450754…
## $ `1999` <dbl> NA, 0.317724562, 3.216121990, 5.085892944, 0.02344117…
## $ `2000` <dbl> NA, 0.391394931, 3.347154483, 3.874847322, 0.02809417…
## $ `2001` <dbl> NA, 0.423255055, 1.764083048, 3.616764917, 0.00920239…
## $ `2002` <dbl> NA, 0.504158418, 0.526683881, 3.442783032, 0.02744460…
## $ `2003` <dbl> NA, 0.471376666, 0.014839347, 3.265931367, 0.00787698…
## $ `2004` <dbl> NA, 0.489006624, 0.000282870, 2.898660515, 0.01810973…
## $ `2005` <dbl> NA, 0.608695844, 0.000428011, 2.446920110, 0.03219485…
## $ `2006` <dbl> NA, 0.885421294, 0.001336931, 3.113633345, 0.09394937…
## $ `2007` <dbl> NA, 0.845182140, 0.001031366, 3.997329793, 0.00014751…
## $ `2008` <dbl> NA, 0.775485842, 0.001132413, 3.590784153, 0.31868380…
## $ `2009` <dbl> 0.265019028, 0.804729858, 0.001390535, 3.344222964, 1…
## $ `2010` <dbl> 0.354491193, 0.848277731, 0.001917839, 4.934621990, 3…
## $ `2011` <dbl> 0.397696521, 1.184875777, 0.002939034, 4.552379054, 5…
## $ `2012` <dbl> 0.386703580, 1.231384811, 0.002668126, 3.969690083, 4…
## $ `2013` <dbl> 0.289482199, 0.902213141, 0.001599583, 3.228200928, 2…
## $ `2014` <dbl> 0.288231475, 0.893874568, 0.001230009, 3.257500653, 2…
## $ `2015` <dbl> 0.29524234, 0.77247401, 0.03924884, 3.83803073, 1.958…
## $ `2016` <dbl> 0.35595122, 0.50149103, 0.03795196, 4.31823948, 2.923…
## $ `2017` <dbl> 0.344837071, 0.483708671, 0.068336179, 3.264792706, 3…
## $ `2018` <dbl> 0.397920793, 0.518595806, 0.092259860, 1.907963892, 3…
## $ `2019` <dbl> 0.362219986, 0.359684399, 0.082064658, 2.072428649, 2…
## $ `2020` <dbl> 0.381654456, 0.278951688, 0.038834747, 2.654465117, 3…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_NRD_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_NRD_LIDC$'2020')
WB_sovereign_ESG_country_groups_NRD_LIDC## # A tibble: 56 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Adjust… NY.ADJ… NA NA NA NA NA NA
## 2 Bangladesh BGD Adjust… NY.ADJ… NA NA NA NA NA NA
## 3 Benin BEN Adjust… NY.ADJ… NA NA NA NA NA NA
## 4 Bhutan BTN Adjust… NY.ADJ… NA NA NA NA NA NA
## 5 Burkina Faso BFA Adjust… NY.ADJ… NA NA NA NA NA NA
## 6 Burundi BDI Adjust… NY.ADJ… NA NA NA NA NA NA
## 7 Cambodia KHM Adjust… NY.ADJ… NA NA NA NA NA NA
## 8 Cameroon CMR Adjust… NY.ADJ… NA NA NA NA NA NA
## 9 Central Afri… CAF Adjust… NY.ADJ… NA NA NA NA NA NA
## 10 Chad TCD Adjust… NY.ADJ… NA NA NA NA NA NA
## # … with 46 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_NRD_LIDC_top10 <- WB_sovereign_ESG_country_groups_NRD_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_NRD_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Natural Resources Depletion - Top 10 LIDCs",
subtitle = "% of GNI, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_NRD_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_NRD_LIDC %>%
filter(`Rank` > 46)
#Chart bottom 10
WB_sovereign_ESG_country_groups_NRD_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Natural Resources Depletion - Bottom 10 LIDCs",
subtitle = "% of GNI, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
3 NAs
Natural Resource Management: Net Forest Depletion
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_NFD_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'NY.ADJ.DFOR.GN.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_NFD_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Adjusted savings: net forest depletion (% of GNI)", …
## $ `Indicator Code` <chr> "NY.ADJ.DFOR.GN.ZS", "NY.ADJ.DFOR.GN.ZS", "NY.ADJ.DFO…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> 0.2794117, NA, 6.7579811, NA, 0.0000000, 6.9655562, 0…
## $ `1971` <dbl> 0.3375673, NA, 5.8471656, NA, 0.0000000, 5.5839502, 0…
## $ `1972` <dbl> 0.3892899, NA, 5.3683169, NA, 0.0000000, 6.6137245, 0…
## $ `1973` <dbl> 0.7517331, 0.4902521, 7.2654359, NA, 0.0000000, 8.970…
## $ `1974` <dbl> 0.7831858, 0.3712633, 7.2703839, NA, 0.0000000, 8.678…
## $ `1975` <dbl> 0.7956867, 0.5521918, 8.2639881, NA, 0.0000000, 9.911…
## $ `1976` <dbl> 0.7569508, 0.6634578, 7.1706735, NA, 0.0000000, 8.187…
## $ `1977` <dbl> 0.589740, 2.431331, 11.978642, NA, 0.000000, 12.67032…
## $ `1978` <dbl> 0.73497110, 1.75248996, 9.87187338, NA, 0.00000000, 1…
## $ `1979` <dbl> 0.55993684, 0.62961579, 7.16010772, NA, 0.00000000, 8…
## $ `1980` <dbl> 0.58168484, 0.66297509, 7.32688047, 17.73283092, 0.00…
## $ `1981` <dbl> 0.43426277, 0.51986939, 6.97322977, 14.89102357, 0.00…
## $ `1982` <dbl> NA, 0.85208142, 10.02046687, 22.47767530, 0.00000000,…
## $ `1983` <dbl> NA, 0.5842947, 7.7791764, 14.7973075, 0.0000000, 6.59…
## $ `1984` <dbl> NA, 0.47811205, 7.46749654, 10.81112139, 0.00000000, …
## $ `1985` <dbl> NA, 0.28629993, 5.46353237, 7.40179954, 0.00000000, 6…
## $ `1986` <dbl> NA, 0.51409623, 6.86825062, 10.29285281, 0.00000000, …
## $ `1987` <dbl> NA, 0.4202785, 5.7680982, 6.9687188, 0.0000000, 9.552…
## $ `1988` <dbl> NA, 0.42199116, 6.09031361, 6.27812106, 0.00000000, 1…
## $ `1989` <dbl> NA, 0.38592916, 6.87235042, 5.97830309, 0.00000000, 1…
## $ `1990` <dbl> NA, 0.41394344, 6.51627052, 6.60075459, 0.00000000, 1…
## $ `1991` <dbl> NA, 0.42337777, 6.44474534, 8.20435432, 0.00000000, 1…
## $ `1992` <dbl> NA, 0.41700364, 7.85104945, 8.61563633, 0.00000000, 1…
## $ `1993` <dbl> NA, 0.32618866, 4.83203758, 7.04205136, 0.00000000, 1…
## $ `1994` <dbl> NA, 0.28628482, 8.17498615, 5.53488815, 0.00000000, 1…
## $ `1995` <dbl> NA, 0.32152129, 8.84051347, 6.60810170, 0.00000000, 2…
## $ `1996` <dbl> NA, 0.26167467, 8.06390287, 6.25656632, 0.00000000, 2…
## $ `1997` <dbl> NA, 0.21644452, 7.81107885, 4.48413591, 0.00000000, 2…
## $ `1998` <dbl> NA, 0.20706543, 7.43227857, 4.77278193, 0.00000000, 2…
## $ `1999` <dbl> NA, 0.20921291, 3.15801806, 5.06886720, 0.00000000, 1…
## $ `2000` <dbl> NA, 0.19467844, 3.27238423, 3.85700725, 0.00000000, 1…
## $ `2001` <dbl> NA, 0.19136793, 1.71405726, 3.57335007, 0.00000000, 1…
## $ `2002` <dbl> NA, 0.1800911, 0.4722776, 3.4143105, 0.0000000, 24.55…
## $ `2003` <dbl> NA, 0.18624791, 0.00000000, 3.24479926, 0.00000000, 4…
## $ `2004` <dbl> NA, 0.17270367, 0.00000000, 2.87657257, 0.00000000, 3…
## $ `2005` <dbl> NA, 0.15556564, 0.00000000, 2.40016564, 0.00000000, 2…
## $ `2006` <dbl> NA, 0.20962145, 0.00000000, 3.06018539, 0.00000000, 2…
## $ `2007` <dbl> NA, 0.31012130, 0.00000000, 3.94234153, 0.00000000, 3…
## $ `2008` <dbl> NA, 0.24350582, 0.00000000, 3.45796000, 0.00000000, 3…
## $ `2009` <dbl> 0.22502632, 0.20929553, 0.00000000, 3.31889090, 0.000…
## $ `2010` <dbl> 0.2886741, 0.3407615, 0.0000000, 4.8793261, 0.0000000…
## $ `2011` <dbl> 0.24932279, 0.32422872, 0.00000000, 4.49048825, 0.000…
## $ `2012` <dbl> 0.21373476, 0.26352378, 0.00000000, 3.91944849, 0.000…
## $ `2013` <dbl> 0.21375019, 0.18943587, 0.00000000, 3.20399757, 0.000…
## $ `2014` <dbl> 0.21713041, 0.18106063, 0.00000000, 3.24468252, 0.000…
## $ `2015` <dbl> 0.24327159, 0.19645972, 0.00000000, 3.82570825, 0.000…
## $ `2016` <dbl> 0.28325658, 0.20491448, 0.00000000, 4.30944637, 0.000…
## $ `2017` <dbl> 0.23157224, 0.15489765, 0.00000000, 3.25427278, 0.000…
## $ `2018` <dbl> 0.24297920, 0.07910001, 0.00000000, 1.89473204, 0.000…
## $ `2019` <dbl> 0.26850821, 0.07908477, 0.00000000, 2.05273817, 0.000…
## $ `2020` <dbl> 0.30825414, 0.08763023, 0.00000000, 2.64047052, 0.000…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_NFD_LIDC <- WB_sovereign_ESG_country_groups_NFD_LIDC[!(is.na(WB_sovereign_ESG_country_groups_NFD_LIDC$"2020") | WB_sovereign_ESG_country_groups_NFD_LIDC$"2020"==""), ]
glimpse(WB_sovereign_ESG_country_groups_NFD_LIDC)## Rows: 56
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Adjusted savings: net forest depletion (% of GNI)", …
## $ `Indicator Code` <chr> "NY.ADJ.DFOR.GN.ZS", "NY.ADJ.DFOR.GN.ZS", "NY.ADJ.DFO…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> 0.2794117, NA, 6.7579811, NA, 0.0000000, 6.9655562, 0…
## $ `1971` <dbl> 0.3375673, NA, 5.8471656, NA, 0.0000000, 5.5839502, 0…
## $ `1972` <dbl> 0.3892899, NA, 5.3683169, NA, 0.0000000, 6.6137245, 0…
## $ `1973` <dbl> 0.7517331, 0.4902521, 7.2654359, NA, 0.0000000, 8.970…
## $ `1974` <dbl> 0.7831858, 0.3712633, 7.2703839, NA, 0.0000000, 8.678…
## $ `1975` <dbl> 0.7956867, 0.5521918, 8.2639881, NA, 0.0000000, 9.911…
## $ `1976` <dbl> 0.7569508, 0.6634578, 7.1706735, NA, 0.0000000, 8.187…
## $ `1977` <dbl> 0.589740, 2.431331, 11.978642, NA, 0.000000, 12.67032…
## $ `1978` <dbl> 0.73497110, 1.75248996, 9.87187338, NA, 0.00000000, 1…
## $ `1979` <dbl> 0.55993684, 0.62961579, 7.16010772, NA, 0.00000000, 8…
## $ `1980` <dbl> 0.58168484, 0.66297509, 7.32688047, 17.73283092, 0.00…
## $ `1981` <dbl> 0.43426277, 0.51986939, 6.97322977, 14.89102357, 0.00…
## $ `1982` <dbl> NA, 0.85208142, 10.02046687, 22.47767530, 0.00000000,…
## $ `1983` <dbl> NA, 0.5842947, 7.7791764, 14.7973075, 0.0000000, 6.59…
## $ `1984` <dbl> NA, 0.47811205, 7.46749654, 10.81112139, 0.00000000, …
## $ `1985` <dbl> NA, 0.28629993, 5.46353237, 7.40179954, 0.00000000, 6…
## $ `1986` <dbl> NA, 0.51409623, 6.86825062, 10.29285281, 0.00000000, …
## $ `1987` <dbl> NA, 0.4202785, 5.7680982, 6.9687188, 0.0000000, 9.552…
## $ `1988` <dbl> NA, 0.42199116, 6.09031361, 6.27812106, 0.00000000, 1…
## $ `1989` <dbl> NA, 0.38592916, 6.87235042, 5.97830309, 0.00000000, 1…
## $ `1990` <dbl> NA, 0.41394344, 6.51627052, 6.60075459, 0.00000000, 1…
## $ `1991` <dbl> NA, 0.42337777, 6.44474534, 8.20435432, 0.00000000, 1…
## $ `1992` <dbl> NA, 0.41700364, 7.85104945, 8.61563633, 0.00000000, 1…
## $ `1993` <dbl> NA, 0.32618866, 4.83203758, 7.04205136, 0.00000000, 1…
## $ `1994` <dbl> NA, 0.28628482, 8.17498615, 5.53488815, 0.00000000, 1…
## $ `1995` <dbl> NA, 0.32152129, 8.84051347, 6.60810170, 0.00000000, 2…
## $ `1996` <dbl> NA, 0.26167467, 8.06390287, 6.25656632, 0.00000000, 2…
## $ `1997` <dbl> NA, 0.21644452, 7.81107885, 4.48413591, 0.00000000, 2…
## $ `1998` <dbl> NA, 0.20706543, 7.43227857, 4.77278193, 0.00000000, 2…
## $ `1999` <dbl> NA, 0.20921291, 3.15801806, 5.06886720, 0.00000000, 1…
## $ `2000` <dbl> NA, 0.19467844, 3.27238423, 3.85700725, 0.00000000, 1…
## $ `2001` <dbl> NA, 0.19136793, 1.71405726, 3.57335007, 0.00000000, 1…
## $ `2002` <dbl> NA, 0.1800911, 0.4722776, 3.4143105, 0.0000000, 24.55…
## $ `2003` <dbl> NA, 0.18624791, 0.00000000, 3.24479926, 0.00000000, 4…
## $ `2004` <dbl> NA, 0.17270367, 0.00000000, 2.87657257, 0.00000000, 3…
## $ `2005` <dbl> NA, 0.15556564, 0.00000000, 2.40016564, 0.00000000, 2…
## $ `2006` <dbl> NA, 0.20962145, 0.00000000, 3.06018539, 0.00000000, 2…
## $ `2007` <dbl> NA, 0.31012130, 0.00000000, 3.94234153, 0.00000000, 3…
## $ `2008` <dbl> NA, 0.24350582, 0.00000000, 3.45796000, 0.00000000, 3…
## $ `2009` <dbl> 0.22502632, 0.20929553, 0.00000000, 3.31889090, 0.000…
## $ `2010` <dbl> 0.2886741, 0.3407615, 0.0000000, 4.8793261, 0.0000000…
## $ `2011` <dbl> 0.24932279, 0.32422872, 0.00000000, 4.49048825, 0.000…
## $ `2012` <dbl> 0.21373476, 0.26352378, 0.00000000, 3.91944849, 0.000…
## $ `2013` <dbl> 0.21375019, 0.18943587, 0.00000000, 3.20399757, 0.000…
## $ `2014` <dbl> 0.21713041, 0.18106063, 0.00000000, 3.24468252, 0.000…
## $ `2015` <dbl> 0.24327159, 0.19645972, 0.00000000, 3.82570825, 0.000…
## $ `2016` <dbl> 0.28325658, 0.20491448, 0.00000000, 4.30944637, 0.000…
## $ `2017` <dbl> 0.23157224, 0.15489765, 0.00000000, 3.25427278, 0.000…
## $ `2018` <dbl> 0.24297920, 0.07910001, 0.00000000, 1.89473204, 0.000…
## $ `2019` <dbl> 0.26850821, 0.07908477, 0.00000000, 2.05273817, 0.000…
## $ `2020` <dbl> 0.30825414, 0.08763023, 0.00000000, 2.64047052, 0.000…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_NFD_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_NFD_LIDC$'2020')
WB_sovereign_ESG_country_groups_NFD_LIDC## # A tibble: 56 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Adjust… NY.ADJ… NA NA NA NA NA NA
## 2 Bangladesh BGD Adjust… NY.ADJ… NA NA NA NA NA NA
## 3 Benin BEN Adjust… NY.ADJ… NA NA NA NA NA NA
## 4 Bhutan BTN Adjust… NY.ADJ… NA NA NA NA NA NA
## 5 Burkina Faso BFA Adjust… NY.ADJ… NA NA NA NA NA NA
## 6 Burundi BDI Adjust… NY.ADJ… NA NA NA NA NA NA
## 7 Cambodia KHM Adjust… NY.ADJ… NA NA NA NA NA NA
## 8 Cameroon CMR Adjust… NY.ADJ… NA NA NA NA NA NA
## 9 Central Afri… CAF Adjust… NY.ADJ… NA NA NA NA NA NA
## 10 Chad TCD Adjust… NY.ADJ… NA NA NA NA NA NA
## # … with 46 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_NFD_LIDC_top10 <- WB_sovereign_ESG_country_groups_NFD_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_NFD_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Net Forest Depletion - Top 10 LIDCs",
subtitle = "% of GNI, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_NFD_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_NFD_LIDC %>%
filter(`Rank` > 46)
#Chart bottom 10
WB_sovereign_ESG_country_groups_NFD_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Net Forest Depletion - Bottom 10 LIDCs",
subtitle = "% of GNI, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
19 countries tied for #1 because they had 0% NFD in 2020 3 NAs
Natural Resource Management: Terrestrial and Marine Protected Areas (% of total territorial area)
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_TMPA_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'ER.PTD.TOTL.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_TMPA_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Terrestrial and marine protected areas (% of total t…
## $ `Indicator Code` <chr> "ER.PTD.TOTL.ZS", "ER.PTD.TOTL.ZS", "ER.PTD.TOTL.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1991` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1992` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1993` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1994` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1995` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1996` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1997` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1998` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1999` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2000` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2001` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2002` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2003` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2004` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2005` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2006` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2007` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2008` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2009` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2010` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2011` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2012` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2013` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2014` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2015` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2016` <dbl> 0.1047070, 4.8886765, 28.8719450, 48.0073122, 15.0848…
## $ `2017` <dbl> 0.1047070, 4.8886486, 23.4719086, 48.0078510, 14.9228…
## $ `2018` <dbl> 0.1047070, 4.8886486, 23.4719086, 48.0078510, 14.9228…
## $ `2019` <dbl> 0.1047070, 4.8885560, 23.4567013, 48.0078507, 14.8904…
## $ `2020` <dbl> 3.6372566, 4.8885560, 23.4571056, 49.6693344, 16.4016…
## $ `2021` <dbl> 3.6372566, 4.8885560, 23.4877701, 49.6693344, 16.4263…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_TMPA_LIDC <- WB_sovereign_ESG_country_groups_TMPA_LIDC[!(is.na(WB_sovereign_ESG_country_groups_TMPA_LIDC$"2020") | WB_sovereign_ESG_country_groups_TMPA_LIDC$"2020"==""), ]
glimpse(WB_sovereign_ESG_country_groups_TMPA_LIDC)## Rows: 58
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Terrestrial and marine protected areas (% of total t…
## $ `Indicator Code` <chr> "ER.PTD.TOTL.ZS", "ER.PTD.TOTL.ZS", "ER.PTD.TOTL.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1991` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1992` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1993` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1994` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1995` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1996` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1997` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1998` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1999` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2000` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2001` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2002` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2003` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2004` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2005` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2006` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2007` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2008` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2009` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2010` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2011` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2012` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2013` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2014` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2015` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2016` <dbl> 0.1047070, 4.8886765, 28.8719450, 48.0073122, 15.0848…
## $ `2017` <dbl> 0.1047070, 4.8886486, 23.4719086, 48.0078510, 14.9228…
## $ `2018` <dbl> 0.1047070, 4.8886486, 23.4719086, 48.0078510, 14.9228…
## $ `2019` <dbl> 0.1047070, 4.8885560, 23.4567013, 48.0078507, 14.8904…
## $ `2020` <dbl> 3.6372566, 4.8885560, 23.4571056, 49.6693344, 16.4016…
## $ `2021` <dbl> 3.6372566, 4.8885560, 23.4877701, 49.6693344, 16.4263…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_TMPA_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_TMPA_LIDC$'2020')
WB_sovereign_ESG_country_groups_TMPA_LIDC## # A tibble: 58 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Terres… ER.PTD… NA NA NA NA NA NA
## 2 Bangladesh BGD Terres… ER.PTD… NA NA NA NA NA NA
## 3 Benin BEN Terres… ER.PTD… NA NA NA NA NA NA
## 4 Bhutan BTN Terres… ER.PTD… NA NA NA NA NA NA
## 5 Burkina Faso BFA Terres… ER.PTD… NA NA NA NA NA NA
## 6 Burundi BDI Terres… ER.PTD… NA NA NA NA NA NA
## 7 Cambodia KHM Terres… ER.PTD… NA NA NA NA NA NA
## 8 Cameroon CMR Terres… ER.PTD… NA NA NA NA NA NA
## 9 Central Afri… CAF Terres… ER.PTD… NA NA NA NA NA NA
## 10 Chad TCD Terres… ER.PTD… NA NA NA NA NA NA
## # … with 48 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_TMPA_LIDC_top10 <- WB_sovereign_ESG_country_groups_TMPA_LIDC %>%
filter(`Rank` > 48)
#Chart top 10
WB_sovereign_ESG_country_groups_TMPA_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, `2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Terrestrial and Marine Protected Areas - Top 10 LIDCs",
subtitle = "% of Total Territorial Area, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_TMPA_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_TMPA_LIDC %>%
filter(`Rank` < 11)
#Chart bottom 10
WB_sovereign_ESG_country_groups_TMPA_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, `2020`),`2020`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Terrestrial and Marine Protected Areas - Bottom 10 LIDCs",
subtitle = "% of Total Territorial Area, 2020",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
1 NA ## Energy Use: Electricity Production From Coal Sources (% of total)
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_EPFC_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EG.ELC.COAL.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_EPFC_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Electricity production from coal sources (% of total…
## $ `Indicator Code` <chr> "EG.ELC.COAL.ZS", "EG.ELC.COAL.ZS", "EG.ELC.COAL.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, 0, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA…
## $ `1972` <dbl> NA, 0, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA…
## $ `1973` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1974` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1975` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1976` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1977` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1978` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1979` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1980` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1981` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1982` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1983` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1984` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1985` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1986` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1987` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1988` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1989` <dbl> NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA,…
## $ `1990` <dbl> NA, 0.0000, 0.0000, NA, NA, NA, NA, 0.0000, NA, NA, N…
## $ `1991` <dbl> NA, 0.00000, 0.00000, NA, NA, NA, NA, 0.00000, NA, NA…
## $ `1992` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, NA, 0.000000, NA,…
## $ `1993` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, NA, 0.000000, NA,…
## $ `1994` <dbl> NA, 0.00000, 0.00000, NA, NA, NA, NA, 0.00000, NA, NA…
## $ `1995` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `1996` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `1997` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `1998` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `1999` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2000` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2001` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2002` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2003` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2004` <dbl> NA, 0.000000, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2005` <dbl> NA, 0.616327, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2006` <dbl> NA, 0.9346111, 0.0000000, NA, NA, NA, 0.0000000, 0.00…
## $ `2007` <dbl> NA, 2.389937, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2008` <dbl> NA, 3.214682, 0.000000, NA, NA, NA, 0.000000, 0.00000…
## $ `2009` <dbl> NA, 2.937300, 0.000000, NA, NA, NA, 2.211690, 0.00000…
## $ `2010` <dbl> NA, 1.892621, 0.000000, NA, NA, NA, 3.100000, 0.00000…
## $ `2011` <dbl> NA, 1.873032, 0.000000, NA, NA, NA, 3.207547, 0.00000…
## $ `2012` <dbl> NA, 1.927433, 0.000000, NA, NA, NA, 2.580195, 0.00000…
## $ `2013` <dbl> NA, 2.306099, 0.000000, NA, NA, NA, 9.505062, 0.00000…
## $ `2014` <dbl> NA, 1.9697377, 0.0000000, NA, NA, NA, 28.1841933, 0.0…
## $ `2015` <dbl> NA, 1.689516, 0.000000, NA, NA, NA, 48.396634, 0.0000…
## $ `2016` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2017` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2018` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2019` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_EPFC_LIDC <- WB_sovereign_ESG_country_groups_EPFC_LIDC[!(is.na(WB_sovereign_ESG_country_groups_EPFC_LIDC$"2015") | WB_sovereign_ESG_country_groups_EPFC_LIDC$"2015"==""), ]
glimpse(WB_sovereign_ESG_country_groups_EPFC_LIDC)## Rows: 32
## Columns: 70
## $ `Country Name` <chr> "Bangladesh", "Benin", "Cambodia", "Cameroon", "Congo…
## $ iso3c <chr> "BGD", "BEN", "KHM", "CMR", "COD", "COG", "CIV", "ERI…
## $ `Indicator Name` <chr> "Electricity production from coal sources (% of total…
## $ `Indicator Code` <chr> "EG.ELC.COAL.ZS", "EG.ELC.COAL.ZS", "EG.ELC.COAL.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> 0.000000, NA, NA, 0.000000, 0.000000, 0.000000, 0.000…
## $ `1972` <dbl> 0.00000000, NA, NA, 0.00000000, 0.00000000, 0.0000000…
## $ `1973` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1974` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1975` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1976` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1977` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1978` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1979` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1980` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1981` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1982` <dbl> 0.000000, 0.000000, NA, 0.000000, 0.000000, 0.000000,…
## $ `1983` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1984` <dbl> 0.0000000, 0.0000000, NA, 0.0000000, 0.0000000, 0.000…
## $ `1985` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1986` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1987` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1988` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1989` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1990` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1991` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1992` <dbl> 0.00000000, 0.00000000, NA, 0.00000000, 0.00000000, 0…
## $ `1993` <dbl> 0.0000000, 0.0000000, NA, 0.0000000, 0.0000000, 0.000…
## $ `1994` <dbl> 0.0000000, 0.0000000, NA, 0.0000000, 0.0000000, 0.000…
## $ `1995` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `1996` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `1997` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `1998` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `1999` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2000` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2001` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2002` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2003` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2004` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2005` <dbl> 0.616327, 0.000000, 0.000000, 0.000000, 0.000000, 0.0…
## $ `2006` <dbl> 0.9346111, 0.0000000, 0.0000000, 0.0000000, 0.0000000…
## $ `2007` <dbl> 2.3899371, 0.0000000, 0.0000000, 0.0000000, 0.0000000…
## $ `2008` <dbl> 3.2146823, 0.0000000, 0.0000000, 0.0000000, 0.0000000…
## $ `2009` <dbl> 2.937300, 0.000000, 2.211690, 0.000000, 0.000000, 0.0…
## $ `2010` <dbl> 1.892621, 0.000000, 3.100000, 0.000000, 0.000000, 0.0…
## $ `2011` <dbl> 1.873032, 0.000000, 3.207547, 0.000000, 0.000000, 0.0…
## $ `2012` <dbl> 1.927433, 0.000000, 2.580195, 0.000000, 0.000000, 0.0…
## $ `2013` <dbl> 2.3060994, 0.0000000, 9.5050619, 0.0000000, 0.0000000…
## $ `2014` <dbl> 1.9697377, 0.0000000, 28.1841933, 0.0000000, 0.000000…
## $ `2015` <dbl> 1.689516, 0.000000, 48.396634, 0.000000, 0.000000, 0.…
## $ `2016` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2017` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2018` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2019` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Bangladesh", "Benin", "Cambodia", "Cameroon", "Congo…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_EPFC_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_EPFC_LIDC$'2015')
WB_sovereign_ESG_country_groups_EPFC_LIDC## # A tibble: 32 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Bangladesh BGD Electr… EG.ELC… NA NA NA NA NA NA
## 2 Benin BEN Electr… EG.ELC… NA NA NA NA NA NA
## 3 Cambodia KHM Electr… EG.ELC… NA NA NA NA NA NA
## 4 Cameroon CMR Electr… EG.ELC… NA NA NA NA NA NA
## 5 Congo, Dem. … COD Electr… EG.ELC… NA NA NA NA NA NA
## 6 Congo, Rep. COG Electr… EG.ELC… NA NA NA NA NA NA
## 7 Cote d'Ivoire CIV Electr… EG.ELC… NA NA NA NA NA NA
## 8 Eritrea ERI Electr… EG.ELC… NA NA NA NA NA NA
## 9 Ethiopia ETH Electr… EG.ELC… NA NA NA NA NA NA
## 10 Ghana GHA Electr… EG.ELC… NA NA NA NA NA NA
## # … with 22 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_EPFC_LIDC_top10 <- WB_sovereign_ESG_country_groups_EPFC_LIDC %>%
filter(`Rank` < 12)
#Chart top 10
WB_sovereign_ESG_country_groups_EPFC_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2015`),`2015`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Electricity Production from Coal - Top 10 LIDCs",
subtitle = "% of Total Electricity Production, 2015",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_EPFC_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_EPFC_LIDC %>%
filter(`Rank` > 22)
#Chart bottom 10
WB_sovereign_ESG_country_groups_EPFC_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2015`),`2015`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Electricity Production from Coal - Bottom 10 LIDCs",
subtitle = "% of Total Electricity Production, 2015",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
22 counries are tied for #1 because they have 0%
27 N/As
Latest data from 2015
Energy Use: Energy Intensity Level of Primary Energy (MJ/$2017 PPP GDP)
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_EIL_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EG.EGY.PRIM.PP.KD') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_EIL_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Energy intensity level of primary energy (MJ/$2017 P…
## $ `Indicator Code` <chr> "EG.EGY.PRIM.PP.KD", "EG.EGY.PRIM.PP.KD", "EG.EGY.PRI…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1991` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1992` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1993` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1994` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1995` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1996` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1997` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1998` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1999` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2000` <dbl> 1.640000, 3.140000, 4.880000, 18.420000, 5.490000, 10…
## $ `2001` <dbl> 1.740000, 3.270000, 4.930000, 17.290000, 5.150000, 10…
## $ `2002` <dbl> 1.400000, 3.230000, 5.050000, 15.990000, 4.210000, 10…
## $ `2003` <dbl> 1.400000, 3.200000, 5.150000, 14.960000, 4.030000, 10…
## $ `2004` <dbl> 1.200000, 3.100000, 5.150000, 14.150000, 4.800000, 9.…
## $ `2005` <dbl> 1.410000, 3.050000, 5.080000, 13.610000, 5.550000, 9.…
## $ `2006` <dbl> 1.500000, 3.050000, 5.760000, 12.990000, 5.600000, 9.…
## $ `2007` <dbl> 1.530000, 2.980000, 5.910000, 11.300000, 5.720000, 8.…
## $ `2008` <dbl> 1.94000, 2.94000, 5.76000, 11.12000, 5.72000, 8.45000…
## $ `2009` <dbl> 2.25000, 2.94000, 5.91000, 10.69000, 5.66000, 8.03000…
## $ `2010` <dbl> 2.460000, 2.930000, 6.000000, 10.110000, 5.420000, 7.…
## $ `2011` <dbl> 3.230000, 2.850000, 5.820000, 9.470000, 5.200000, 7.7…
## $ `2012` <dbl> 2.610000, 2.770000, 5.610000, 9.510000, 5.150000, 7.4…
## $ `2013` <dbl> 2.460000, 2.730000, 5.710000, 9.410000, 5.040000, 7.4…
## $ `2014` <dbl> 2.250000, 2.660000, 5.540000, 9.320000, 4.910000, 7.0…
## $ `2015` <dbl> 2.370000, 2.690000, 5.790000, 8.700000, 4.940000, 7.3…
## $ `2016` <dbl> 2.24, 2.61, 6.22, 8.30, 4.76, 7.56, 4.74, 4.65, 9.12,…
## $ `2017` <dbl> 2.30, 2.50, 6.11, 8.06, 4.72, 7.62, 4.59, 4.53, 8.80,…
## $ `2018` <dbl> 2.44, 2.30, 6.05, 8.22, 4.60, 7.71, 4.61, 4.43, 8.56,…
## $ `2019` <dbl> 2.41, 2.36, 5.69, 7.91, 4.49, 7.62, 4.68, 4.33, 8.39,…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_EIL_LIDC <- WB_sovereign_ESG_country_groups_EIL_LIDC[!(is.na(WB_sovereign_ESG_country_groups_EIL_LIDC$"2019") | WB_sovereign_ESG_country_groups_EIL_LIDC$"2019"==""), ]
glimpse(WB_sovereign_ESG_country_groups_EIL_LIDC)## Rows: 56
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Energy intensity level of primary energy (MJ/$2017 P…
## $ `Indicator Code` <chr> "EG.EGY.PRIM.PP.KD", "EG.EGY.PRIM.PP.KD", "EG.EGY.PRI…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1991` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1992` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1993` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1994` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1995` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1996` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1997` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1998` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1999` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2000` <dbl> 1.64, 3.14, 4.88, 18.42, 5.49, 10.37, 7.91, 6.23, 7.7…
## $ `2001` <dbl> 1.74, 3.27, 4.93, 17.29, 5.15, 10.52, 7.51, 6.04, 7.5…
## $ `2002` <dbl> 1.40, 3.23, 5.05, 15.99, 4.21, 10.07, 7.05, 6.10, 7.3…
## $ `2003` <dbl> 1.40, 3.20, 5.15, 14.96, 4.03, 10.05, 6.69, 6.07, 7.9…
## $ `2004` <dbl> 1.20, 3.10, 5.15, 14.15, 4.80, 9.66, 6.23, 5.86, 7.65…
## $ `2005` <dbl> 1.41, 3.05, 5.08, 13.61, 5.55, 9.48, 5.73, 5.79, 7.74…
## $ `2006` <dbl> 1.50, 3.05, 5.76, 12.99, 5.60, 9.05, 5.31, 5.17, 7.59…
## $ `2007` <dbl> 1.53, 2.98, 5.91, 11.30, 5.72, 8.83, 5.03, 4.65, 7.47…
## $ `2008` <dbl> 1.94, 2.94, 5.76, 11.12, 5.72, 8.45, 4.76, 4.53, 7.33…
## $ `2009` <dbl> 2.25, 2.94, 5.91, 10.69, 5.66, 8.03, 5.07, 4.80, 6.89…
## $ `2010` <dbl> 2.46, 2.93, 6.00, 10.11, 5.42, 7.93, 5.05, 4.68, 6.76…
## $ `2011` <dbl> 3.23, 2.85, 5.82, 9.47, 5.20, 7.77, 4.81, 4.71, 6.68,…
## $ `2012` <dbl> 2.61, 2.77, 5.61, 9.51, 5.15, 7.41, 4.68, 4.70, 6.25,…
## $ `2013` <dbl> 2.46, 2.73, 5.71, 9.41, 5.04, 7.42, 4.47, 4.67, 9.30,…
## $ `2014` <dbl> 2.25, 2.66, 5.54, 9.32, 4.91, 7.08, 4.50, 4.78, 9.55,…
## $ `2015` <dbl> 2.37, 2.69, 5.79, 8.70, 4.94, 7.38, 4.58, 4.77, 9.40,…
## $ `2016` <dbl> 2.24, 2.61, 6.22, 8.30, 4.76, 7.56, 4.74, 4.65, 9.12,…
## $ `2017` <dbl> 2.30, 2.50, 6.11, 8.06, 4.72, 7.62, 4.59, 4.53, 8.80,…
## $ `2018` <dbl> 2.44, 2.30, 6.05, 8.22, 4.60, 7.71, 4.61, 4.43, 8.56,…
## $ `2019` <dbl> 2.41, 2.36, 5.69, 7.91, 4.49, 7.62, 4.68, 4.33, 8.39,…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_EIL_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_EIL_LIDC$'2019')
WB_sovereign_ESG_country_groups_EIL_LIDC## # A tibble: 56 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Energy… EG.EGY… NA NA NA NA NA NA
## 2 Bangladesh BGD Energy… EG.EGY… NA NA NA NA NA NA
## 3 Benin BEN Energy… EG.EGY… NA NA NA NA NA NA
## 4 Bhutan BTN Energy… EG.EGY… NA NA NA NA NA NA
## 5 Burkina Faso BFA Energy… EG.EGY… NA NA NA NA NA NA
## 6 Burundi BDI Energy… EG.EGY… NA NA NA NA NA NA
## 7 Cambodia KHM Energy… EG.EGY… NA NA NA NA NA NA
## 8 Cameroon CMR Energy… EG.EGY… NA NA NA NA NA NA
## 9 Central Afri… CAF Energy… EG.EGY… NA NA NA NA NA NA
## 10 Chad TCD Energy… EG.EGY… NA NA NA NA NA NA
## # … with 46 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_EIL_LIDC_top10 <- WB_sovereign_ESG_country_groups_EIL_LIDC %>%
filter(`Rank` < 11)
#Chart top 10
WB_sovereign_ESG_country_groups_EIL_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Energy Intensity Level of Primary Energy - Top 10 LIDCs",
subtitle = "MJ/$2017 PPP GDP, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_EIL_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_EIL_LIDC %>%
filter(`Rank` > 46)
#Chart bottom 10
WB_sovereign_ESG_country_groups_EIL_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, -`2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Energy Intensity Level of Primary Energy - Bottom 10 LIDCs",
subtitle = "MJ/$2017 PPP GDP, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
3 NAs
Energy Use: Renewable Electricity Output (% of total electricity output)
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_REO_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EG.ELC.RNEW.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_REO_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Renewable electricity output (% of total electricity…
## $ `Indicator Code` <chr> "EG.ELC.RNEW.ZS", "EG.ELC.RNEW.ZS", "EG.ELC.RNEW.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 67.730496, 11.433006, 0.000000, 99.552430, 4.891304, …
## $ `1991` <dbl> 67.980296, 10.133011, 0.000000, 99.744246, 6.701031, …
## $ `1992` <dbl> 67.994310, 8.949854, 0.000000, 99.936061, 9.950249, 9…
## $ `1993` <dbl> 68.345324, 6.604388, 0.000000, 99.940618, 21.860465, …
## $ `1994` <dbl> 68.704512, 8.656991, 0.000000, 99.940688, 33.796296, …
## $ `1995` <dbl> 69.037037, 3.442532, 0.000000, 100.000000, 38.699053,…
## $ `1996` <dbl> 70.370370, 6.440648, 0.000000, 100.000000, 26.983547,…
## $ `1997` <dbl> 72.3880597, 6.0634171, 3.3898305, 100.0000000, 20.084…
## $ `1998` <dbl> 74.4360902, 6.7147958, 2.5316456, 100.0000000, 23.158…
## $ `1999` <dbl> 73.7226277, 5.7647059, 2.7777778, 100.0000000, 34.648…
## $ `2000` <dbl> 74.9890941, 4.7492233, 2.3809524, 100.0000000, 25.179…
## $ `2001` <dbl> 72.8114600, 5.7095216, 3.0303030, 99.9781490, 14.7195…
## $ `2002` <dbl> 79.0639712, 4.0128583, 3.1746032, 99.9586535, 17.4938…
## $ `2003` <dbl> 70.2497286, 3.7997159, 2.5000000, 99.9169665, 21.5699…
## $ `2004` <dbl> 70.8908407, 3.0344772, 1.2345679, 99.9235604, 21.4451…
## $ `2005` <dbl> 74.0618101, 2.8320793, 0.9345794, 99.9433428, 19.4654…
## $ `2006` <dbl> 70.7557503, 2.5363178, 2.5974026, 99.9601840, 14.6221…
## $ `2007` <dbl> 72.0000000, 2.4157394, 1.3636364, 99.9695215, 18.1372…
## $ `2008` <dbl> 68.6548223, 2.7763166, 1.3100437, 99.9985635, 21.9405…
## $ `2009` <dbl> 87.1766029, 1.1216612, 0.7812500, 99.9985710, 18.9054…
## $ `2010` <dbl> 85.9865471, 1.7872027, 0.8695652, 99.9959063, 20.7854…
## $ `2011` <dbl> 82.4875622, 1.9749507, 0.0000000, 99.9957552, 15.4557…
## $ `2012` <dbl> 85.9099804, 1.6000165, 0.0000000, 99.9970703, 15.4560…
## $ `2013` <dbl> 78.6364081, 1.9465361, 0.0000000, 99.9934556, 14.4382…
## $ `2014` <dbl> 85.3235490, 1.3197242, 0.0000000, 99.9928611, 10.3971…
## $ `2015` <dbl> 86.0501113, 1.2268899, 5.5555556, 99.9935464, 9.35403…
## $ `2016` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2017` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2018` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2019` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_REO_LIDC <- WB_sovereign_ESG_country_groups_REO_LIDC[!(is.na(WB_sovereign_ESG_country_groups_REO_LIDC$"2015") | WB_sovereign_ESG_country_groups_REO_LIDC$"2015"==""), ]
glimpse(WB_sovereign_ESG_country_groups_REO_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Renewable electricity output (% of total electricity…
## $ `Indicator Code` <chr> "EG.ELC.RNEW.ZS", "EG.ELC.RNEW.ZS", "EG.ELC.RNEW.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 67.730496, 11.433006, 0.000000, 99.552430, 4.891304, …
## $ `1991` <dbl> 67.980296, 10.133011, 0.000000, 99.744246, 6.701031, …
## $ `1992` <dbl> 67.994310, 8.949854, 0.000000, 99.936061, 9.950249, 9…
## $ `1993` <dbl> 68.345324, 6.604388, 0.000000, 99.940618, 21.860465, …
## $ `1994` <dbl> 68.704512, 8.656991, 0.000000, 99.940688, 33.796296, …
## $ `1995` <dbl> 69.037037, 3.442532, 0.000000, 100.000000, 38.699053,…
## $ `1996` <dbl> 70.370370, 6.440648, 0.000000, 100.000000, 26.983547,…
## $ `1997` <dbl> 72.3880597, 6.0634171, 3.3898305, 100.0000000, 20.084…
## $ `1998` <dbl> 74.4360902, 6.7147958, 2.5316456, 100.0000000, 23.158…
## $ `1999` <dbl> 73.7226277, 5.7647059, 2.7777778, 100.0000000, 34.648…
## $ `2000` <dbl> 74.9890941, 4.7492233, 2.3809524, 100.0000000, 25.179…
## $ `2001` <dbl> 72.8114600, 5.7095216, 3.0303030, 99.9781490, 14.7195…
## $ `2002` <dbl> 79.0639712, 4.0128583, 3.1746032, 99.9586535, 17.4938…
## $ `2003` <dbl> 70.2497286, 3.7997159, 2.5000000, 99.9169665, 21.5699…
## $ `2004` <dbl> 70.8908407, 3.0344772, 1.2345679, 99.9235604, 21.4451…
## $ `2005` <dbl> 74.0618101, 2.8320793, 0.9345794, 99.9433428, 19.4654…
## $ `2006` <dbl> 70.7557503, 2.5363178, 2.5974026, 99.9601840, 14.6221…
## $ `2007` <dbl> 72.0000000, 2.4157394, 1.3636364, 99.9695215, 18.1372…
## $ `2008` <dbl> 68.6548223, 2.7763166, 1.3100437, 99.9985635, 21.9405…
## $ `2009` <dbl> 87.1766029, 1.1216612, 0.7812500, 99.9985710, 18.9054…
## $ `2010` <dbl> 85.9865471, 1.7872027, 0.8695652, 99.9959063, 20.7854…
## $ `2011` <dbl> 82.4875622, 1.9749507, 0.0000000, 99.9957552, 15.4557…
## $ `2012` <dbl> 85.9099804, 1.6000165, 0.0000000, 99.9970703, 15.4560…
## $ `2013` <dbl> 78.6364081, 1.9465361, 0.0000000, 99.9934556, 14.4382…
## $ `2014` <dbl> 85.3235490, 1.3197242, 0.0000000, 99.9928611, 10.3971…
## $ `2015` <dbl> 86.0501113, 1.2268899, 5.5555556, 99.9935464, 9.35403…
## $ `2016` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2017` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2018` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2019` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_REO_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_REO_LIDC$'2015')
WB_sovereign_ESG_country_groups_REO_LIDC## # A tibble: 59 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Renewa… EG.ELC… NA NA NA NA NA NA
## 2 Bangladesh BGD Renewa… EG.ELC… NA NA NA NA NA NA
## 3 Benin BEN Renewa… EG.ELC… NA NA NA NA NA NA
## 4 Bhutan BTN Renewa… EG.ELC… NA NA NA NA NA NA
## 5 Burkina Faso BFA Renewa… EG.ELC… NA NA NA NA NA NA
## 6 Burundi BDI Renewa… EG.ELC… NA NA NA NA NA NA
## 7 Cambodia KHM Renewa… EG.ELC… NA NA NA NA NA NA
## 8 Cameroon CMR Renewa… EG.ELC… NA NA NA NA NA NA
## 9 Central Afri… CAF Renewa… EG.ELC… NA NA NA NA NA NA
## 10 Chad TCD Renewa… EG.ELC… NA NA NA NA NA NA
## # … with 49 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_REO_LIDC_top10 <- WB_sovereign_ESG_country_groups_REO_LIDC %>%
filter(`Rank` > 49)
#Chart top 10
WB_sovereign_ESG_country_groups_REO_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, `2015`),`2015`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Renewable Electricity Output - Top 10 LIDCs",
subtitle = "% of Total Electricity Output, 2015",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_REO_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_REO_LIDC %>%
filter(`Rank` < 11)
#Chart bottom 10
WB_sovereign_ESG_country_groups_REO_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, `2015`),`2015`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Renewable Electricity Output - Bottom 10 LIDCs",
subtitle = "% of Total Electricity Output, 2015",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
xxx
9 countries tied for worst with 0% renewable electricity output
Latest data from 2015
No NAs
Energy Use: Renewable Energy Consumption (% of total final energy consumption)
#Filter merged dataset for indicator and LIDCs
WB_sovereign_ESG_country_groups_REC_LIDC <- WB_sovereign_ESG_country_groups %>%
filter(`Indicator Code` == 'EG.FEC.RNEW.ZS') %>%
filter(country_group == 'Low-Income Developing Countries')
glimpse(WB_sovereign_ESG_country_groups_REC_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Renewable energy consumption (% of total final energ…
## $ `Indicator Code` <chr> "EG.FEC.RNEW.ZS", "EG.FEC.RNEW.ZS", "EG.FEC.RNEW.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 15.924532, 71.664971, 93.703241, 95.898852, 93.158060…
## $ `1991` <dbl> 17.036444, 73.159667, 94.964848, 95.919938, 93.253823…
## $ `1992` <dbl> 26.52163, 71.66070, 94.85184, 95.28749, 93.29010, 94.…
## $ `1993` <dbl> 30.585667, 70.557123, 94.988801, 95.858075, 93.479993…
## $ `1994` <dbl> 32.796251, 68.979907, 94.975035, 95.290964, 93.608094…
## $ `1995` <dbl> 35.075640, 63.802809, 94.771987, 94.371750, 93.140200…
## $ `1996` <dbl> 37.945748, 62.124077, 84.145968, 93.240021, 92.156594…
## $ `1997` <dbl> 41.432601, 59.972856, 80.626432, 91.350064, 91.390955…
## $ `1998` <dbl> 44.094337, 60.233971, 79.568432, 91.531471, 91.012549…
## $ `1999` <dbl> 52.185774, 60.534396, 76.905425, 91.565623, 86.854917…
## $ `2000` <dbl> 44.99, 59.06, 70.29, 91.40, 85.41, 93.23, 81.58, 84.5…
## $ `2001` <dbl> 45.60, 55.82, 66.86, 91.75, 83.68, 94.84, 80.51, 85.3…
## $ `2002` <dbl> 37.83, 54.33, 64.04, 91.20, 79.34, 94.65, 80.97, 85.2…
## $ `2003` <dbl> 36.66, 52.62, 61.73, 91.92, 79.08, 95.76, 79.92, 85.3…
## $ `2004` <dbl> 44.24, 52.05, 60.69, 93.46, 83.53, 96.04, 80.69, 85.5…
## $ `2005` <dbl> 33.88, 50.66, 59.20, 91.67, 86.54, 96.01, 79.24, 86.3…
## $ `2006` <dbl> 31.89, 48.69, 57.31, 91.92, 84.62, 95.31, 78.01, 85.5…
## $ `2007` <dbl> 28.78, 47.19, 54.49, 92.07, 82.43, 95.29, 74.79, 80.8…
## $ `2008` <dbl> 21.17, 45.20, 54.76, 91.81, 82.94, 95.15, 74.13, 80.8…
## $ `2009` <dbl> 16.53, 43.10, 52.83, 92.38, 83.60, 95.18, 68.04, 79.2…
## $ `2010` <dbl> 15.15, 40.28, 47.19, 90.80, 81.45, 92.57, 64.82, 78.7…
## $ `2011` <dbl> 12.61, 38.41, 48.70, 89.01, 80.57, 91.65, 63.99, 78.6…
## $ `2012` <dbl> 15.36, 37.31, 50.33, 87.32, 77.18, 91.45, 64.36, 78.5…
## $ `2013` <dbl> 16.86, 37.08, 51.97, 86.70, 75.43, 91.08, 64.97, 77.6…
## $ `2014` <dbl> 18.93, 35.32, 51.05, 86.54, 75.24, 91.28, 63.70, 76.7…
## $ `2015` <dbl> 17.53, 31.93, 49.94, 86.68, 72.71, 91.15, 60.63, 78.0…
## $ `2016` <dbl> 19.92, 30.49, 45.42, 85.02, 72.27, 89.52, 58.01, 78.7…
## $ `2017` <dbl> 19.21, 28.36, 45.38, 83.63, 69.08, 88.12, 56.25, 79.1…
## $ `2018` <dbl> 17.96, 26.88, 43.97, 82.22, 66.97, 85.58, 56.38, 79.2…
## $ `2019` <dbl> 18.51, 24.75, 46.47, 82.27, 64.85, 84.77, 53.36, 79.4…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Remove any NAs
WB_sovereign_ESG_country_groups_REC_LIDC <- WB_sovereign_ESG_country_groups_REC_LIDC[!(is.na(WB_sovereign_ESG_country_groups_REC_LIDC$"2019") | WB_sovereign_ESG_country_groups_REC_LIDC$"2019"==""), ]
glimpse(WB_sovereign_ESG_country_groups_REC_LIDC)## Rows: 59
## Columns: 70
## $ `Country Name` <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ iso3c <chr> "AFG", "BGD", "BEN", "BTN", "BFA", "BDI", "KHM", "CMR…
## $ `Indicator Name` <chr> "Renewable energy consumption (% of total final energ…
## $ `Indicator Code` <chr> "EG.FEC.RNEW.ZS", "EG.FEC.RNEW.ZS", "EG.FEC.RNEW.ZS",…
## $ `1960` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1962` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1963` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1964` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1965` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1966` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1967` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1968` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1969` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1970` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1971` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1972` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1973` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1974` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1975` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1976` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1977` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1978` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1979` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1980` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1981` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1982` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1983` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1984` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1985` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1986` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1987` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1988` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `1990` <dbl> 15.924532, 71.664971, 93.703241, 95.898852, 93.158060…
## $ `1991` <dbl> 17.036444, 73.159667, 94.964848, 95.919938, 93.253823…
## $ `1992` <dbl> 26.52163, 71.66070, 94.85184, 95.28749, 93.29010, 94.…
## $ `1993` <dbl> 30.585667, 70.557123, 94.988801, 95.858075, 93.479993…
## $ `1994` <dbl> 32.796251, 68.979907, 94.975035, 95.290964, 93.608094…
## $ `1995` <dbl> 35.075640, 63.802809, 94.771987, 94.371750, 93.140200…
## $ `1996` <dbl> 37.945748, 62.124077, 84.145968, 93.240021, 92.156594…
## $ `1997` <dbl> 41.432601, 59.972856, 80.626432, 91.350064, 91.390955…
## $ `1998` <dbl> 44.094337, 60.233971, 79.568432, 91.531471, 91.012549…
## $ `1999` <dbl> 52.185774, 60.534396, 76.905425, 91.565623, 86.854917…
## $ `2000` <dbl> 44.99, 59.06, 70.29, 91.40, 85.41, 93.23, 81.58, 84.5…
## $ `2001` <dbl> 45.60, 55.82, 66.86, 91.75, 83.68, 94.84, 80.51, 85.3…
## $ `2002` <dbl> 37.83, 54.33, 64.04, 91.20, 79.34, 94.65, 80.97, 85.2…
## $ `2003` <dbl> 36.66, 52.62, 61.73, 91.92, 79.08, 95.76, 79.92, 85.3…
## $ `2004` <dbl> 44.24, 52.05, 60.69, 93.46, 83.53, 96.04, 80.69, 85.5…
## $ `2005` <dbl> 33.88, 50.66, 59.20, 91.67, 86.54, 96.01, 79.24, 86.3…
## $ `2006` <dbl> 31.89, 48.69, 57.31, 91.92, 84.62, 95.31, 78.01, 85.5…
## $ `2007` <dbl> 28.78, 47.19, 54.49, 92.07, 82.43, 95.29, 74.79, 80.8…
## $ `2008` <dbl> 21.17, 45.20, 54.76, 91.81, 82.94, 95.15, 74.13, 80.8…
## $ `2009` <dbl> 16.53, 43.10, 52.83, 92.38, 83.60, 95.18, 68.04, 79.2…
## $ `2010` <dbl> 15.15, 40.28, 47.19, 90.80, 81.45, 92.57, 64.82, 78.7…
## $ `2011` <dbl> 12.61, 38.41, 48.70, 89.01, 80.57, 91.65, 63.99, 78.6…
## $ `2012` <dbl> 15.36, 37.31, 50.33, 87.32, 77.18, 91.45, 64.36, 78.5…
## $ `2013` <dbl> 16.86, 37.08, 51.97, 86.70, 75.43, 91.08, 64.97, 77.6…
## $ `2014` <dbl> 18.93, 35.32, 51.05, 86.54, 75.24, 91.28, 63.70, 76.7…
## $ `2015` <dbl> 17.53, 31.93, 49.94, 86.68, 72.71, 91.15, 60.63, 78.0…
## $ `2016` <dbl> 19.92, 30.49, 45.42, 85.02, 72.27, 89.52, 58.01, 78.7…
## $ `2017` <dbl> 19.21, 28.36, 45.38, 83.63, 69.08, 88.12, 56.25, 79.1…
## $ `2018` <dbl> 17.96, 26.88, 43.97, 82.22, 66.97, 85.58, 56.38, 79.2…
## $ `2019` <dbl> 18.51, 24.75, 46.47, 82.27, 64.85, 84.77, 53.36, 79.4…
## $ `2020` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2021` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ `2050` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ country_name <chr> "Afghanistan", "Bangladesh", "Benin", "Bhutan", "Burk…
## $ country_group <chr> "Low-Income Developing Countries", "Low-Income Develo…
## $ group_type <chr> "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF", "IMF…#Rank countries by indicator performance
WB_sovereign_ESG_country_groups_REC_LIDC$Rank<-rank(WB_sovereign_ESG_country_groups_REC_LIDC$'2019')
WB_sovereign_ESG_country_groups_REC_LIDC## # A tibble: 59 × 71
## Country Nam…¹ iso3c Indic…² Indic…³ `1960` `1961` `1962` `1963` `1964` `1965`
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Afghanistan AFG Renewa… EG.FEC… NA NA NA NA NA NA
## 2 Bangladesh BGD Renewa… EG.FEC… NA NA NA NA NA NA
## 3 Benin BEN Renewa… EG.FEC… NA NA NA NA NA NA
## 4 Bhutan BTN Renewa… EG.FEC… NA NA NA NA NA NA
## 5 Burkina Faso BFA Renewa… EG.FEC… NA NA NA NA NA NA
## 6 Burundi BDI Renewa… EG.FEC… NA NA NA NA NA NA
## 7 Cambodia KHM Renewa… EG.FEC… NA NA NA NA NA NA
## 8 Cameroon CMR Renewa… EG.FEC… NA NA NA NA NA NA
## 9 Central Afri… CAF Renewa… EG.FEC… NA NA NA NA NA NA
## 10 Chad TCD Renewa… EG.FEC… NA NA NA NA NA NA
## # … with 49 more rows, 61 more variables: `1966` <dbl>, `1967` <dbl>,
## # `1968` <dbl>, `1969` <dbl>, `1970` <dbl>, `1971` <dbl>, `1972` <dbl>,
## # `1973` <dbl>, `1974` <dbl>, `1975` <dbl>, `1976` <dbl>, `1977` <dbl>,
## # `1978` <dbl>, `1979` <dbl>, `1980` <dbl>, `1981` <dbl>, `1982` <dbl>,
## # `1983` <dbl>, `1984` <dbl>, `1985` <dbl>, `1986` <dbl>, `1987` <dbl>,
## # `1988` <dbl>, `1989` <dbl>, `1990` <dbl>, `1991` <dbl>, `1992` <dbl>,
## # `1993` <dbl>, `1994` <dbl>, `1995` <dbl>, `1996` <dbl>, `1997` <dbl>, …#Filter top 10
WB_sovereign_ESG_country_groups_REC_LIDC_top10 <- WB_sovereign_ESG_country_groups_REC_LIDC %>%
filter(`Rank` > 49)
#Chart top 10
WB_sovereign_ESG_country_groups_REC_LIDC_top10 %>%
ggplot(aes(fct_reorder(iso3c, `2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Renewable Electricity Consumption - Top 10 LIDCs",
subtitle = "% of Total Final Electricity Consumption, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
#Filter bottom 10
WB_sovereign_ESG_country_groups_REC_LIDC_bottom10 <- WB_sovereign_ESG_country_groups_REC_LIDC %>%
filter(`Rank` < 11)
#Chart bottom 10
WB_sovereign_ESG_country_groups_REC_LIDC_bottom10 %>%
ggplot(aes(fct_reorder(iso3c, `2019`),`2019`)) +
geom_col() +
coord_flip() +
scale_y_continuous(labels = )+
scale_x_discrete (guide = guide_axis(n.dodge=1.75))+
labs(
x = "",
y = "",
title = "Renewable Electricity Consumption - Bottom 10 LIDCs",
subtitle = "% of Total Final Electricity Consumption, 2019",
caption = "Data source: World Bank Sovereign ESG Data"
)+
theme_pander()
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No NAs
Key Findings
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