Warning: One or more parsing issues, call `problems()` on your data frame for details,
e.g.:
dat <- vroom(...)
problems(dat)
Rows: 2 Columns: 1
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): RDX3
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.
Rows: 5275 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): iso2c, iso3c, country, region, income
dbl (5): year, gdp_percap, population, birth_rate, neonat_mortal_rate
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.
head(nations)
# A tibble: 6 × 10
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
# ℹ 2 more variables: region <chr>, income <chr>
# A tibble: 6 × 10
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AE ARE United … 1991 73037. 1913190 24.6 7.9
2 AE ARE United … 1993 71960. 2127863 22.4 7.3
3 AE ARE United … 2001 83534. 3217865 15.8 5.5
4 AE ARE United … 1992 73154. 2019014 23.5 7.6
5 AE ARE United … 1994 74684. 2238281 21.3 6.9
6 AE ARE United … 2007 75427. 6010100 12.8 4.7
# ℹ 2 more variables: region <chr>, income <chr>
Rows: 5275 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): iso2c, iso3c, country, region, income
dbl (5): year, gdp_percap, population, birth_rate, neonat_mortal_rate
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.
head(nations)
# A tibble: 6 × 11
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
# ℹ 3 more variables: region <chr>, income <chr>, gdp_tod <dbl>
summary(nations)
iso2c iso3c country year
Length:5275 Length:5275 Length:5275 Min. :1990
Class :character Class :character Class :character 1st Qu.:1996
Mode :character Mode :character Mode :character Median :2002
Mean :2002
3rd Qu.:2008
Max. :2014
gdp_percap population birth_rate neonat_mortal_rate
Min. : 239.7 Min. :9.004e+03 Min. : 6.90 Min. : 0.70
1st Qu.: 2263.6 1st Qu.:7.175e+05 1st Qu.:13.40 1st Qu.: 6.70
Median : 6563.2 Median :5.303e+06 Median :21.60 Median :15.00
Mean : 12788.8 Mean :2.958e+07 Mean :24.16 Mean :19.40
3rd Qu.: 17195.0 3rd Qu.:1.757e+07 3rd Qu.:33.88 3rd Qu.:29.48
Max. :141968.1 Max. :1.364e+09 Max. :55.12 Max. :73.10
NA's :766 NA's :14 NA's :295 NA's :525
region income gdp_tod
Length:5275 Length:5275 Min. : 0.0000
Class :character Class :character 1st Qu.: 0.0077
Mode :character Mode :character Median : 0.0324
Mean : 0.3259
3rd Qu.: 0.1849
Max. :18.0829
NA's :766
Chart 1 represent 3 East africa countries and South Africa
# A tibble: 6 × 11
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 KE KEN Kenya 1990 1536. 23446229 42.2 27.4
2 TZ TZA Tanzania 1990 952. 25458208 44.1 39.5
3 UG UGA Uganda 1990 500. 17384369 49.8 38.5
4 ZA ZAF South A… 1990 6698. 35200000 29.3 20.4
5 KE KEN Kenya 1991 1557. 24234087 41.1 27.2
6 TZ TZA Tanzania 1991 972. 26307482 43.7 38.8
# ℹ 3 more variables: region <chr>, income <chr>, gdp_tod <dbl>
ggplot(east_africa_sa, aes(x = year, y = gdp_tod, color = country) ) +geom_line() +geom_point() +ggtitle("Kenya's Position in East Africa and it's Comparison with South Africa") +xlab("year") +ylab("GDP ($ trillion)") +scale_color_brewer(palette ="Set1") +theme(legend.title =element_blank(), legend.key =element_rect() ) +theme(panel.background =element_rect(fill ="white",colour ="white") ) +theme(panel.grid.major =element_line(size =0.6, linetype ='solid', colour ="#f0f0f0") ) +theme(panel.grid.minor =element_line(size =0.6, linetype ='solid', colour ="#f0f0f0") )
Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
ℹ Please use the `linewidth` argument instead.
I’ve chosen to analyze my country’s situation by examining East African countries. Kenya recently engaged in discussions with South Africa, resulting in an agreement that facilitates trade between the two nations. This development has also simplified travel for Kenyan citizens to South Africa. Consequently, I decided to investigate how Kenya is performing in comparison to South Africa.
`summarise()` has grouped output by 'year'. You can override using the
`.groups` argument.
head(by_region)
# A tibble: 6 × 3
# Groups: year [1]
year region GDP
<dbl> <chr> <dbl>
1 1990 East Asia & Pacific 5.52
2 1990 Europe & Central Asia 9.36
3 1990 Latin America & Caribbean 2.40
4 1990 Middle East & North Africa 1.66
5 1990 North America 6.54
6 1990 South Asia 1.35
chat2 <-ggplot(by_region, aes(x = year, y = GDP, fill = region)) +geom_area(color ="black") +ggtitle("GDP by World Bank Region") +ylab("GDP ($ trillion)") +xlab("Year") +scale_fill_brewer(palette ="Set2") +theme(panel.background =element_rect(fill ="white",colour ="white") ) +theme(panel.grid.major =element_line(size =0.6, linetype ='solid', colour ="#f0f0f0") ) +theme(panel.grid.minor =element_line(size =0.6, linetype ='solid', colour ="#f0f0f0") ) chat2
