Activity 9
Sarah Stuck
2022-11-03
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4
## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.0 ✔ stringr 1.4.1
## ✔ readr 2.1.2 ✔ forcats 0.5.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(skimr)
library(ggthemes)Importing the data
# Observed annual average temperatures for the Lower 48 states
tempState <- read_csv("https://raw.githubusercontent.com/washingtonpost/data-2C-beyond-the-limit-usa/main/data/processed/climdiv_state_year.csv")## Rows: 6000 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): fips
## dbl (3): year, temp, tempc
##
## 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.# Observed annual average temperatures for counties in the Lower 48 states
tempCounty <- read_csv("https://raw.githubusercontent.com/washingtonpost/data-2C-beyond-the-limit-usa/main/data/processed/climdiv_county_year.csv")## Rows: 388375 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): fips
## dbl (3): year, temp, tempc
##
## 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.# Temperature change estimates for each of the Lower 48 states
tempChangeState <- read_csv("https://github.com/washingtonpost/data-2C-beyond-the-limit-usa/raw/main/data/processed/model_state.csv")## Rows: 48 Columns: 10
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (5): fips, max_warming_season, STUSAB, STATE_NAME, STATENS
## dbl (5): Fall, Spring, Summer, Winter, Annual
##
## 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.# Temperature change estimates for counties in the contiguous U.S.
tempChangeCounty <- read_csv("https://github.com/washingtonpost/data-2C-beyond-the-limit-usa/raw/main/data/processed/model_county.csv")## Rows: 3107 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): fips, max_warming_season, CTYNAME, STNAME
## dbl (5): Fall, Spring, Summer, Winter, Annual
##
## 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.glimpse(tempState)## Rows: 6,000
## Columns: 4
## $ fips <chr> "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01"…
## $ year <dbl> 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905…
## $ temp <dbl> 61.64167, 64.26667, 64.19167, 62.98333, 63.10000, 63.40833, 61.3…
## $ tempc <dbl> 16.46759, 17.92593, 17.88426, 17.21296, 17.27778, 17.44907, 16.3…glimpse(tempCounty)## Rows: 388,375
## Columns: 4
## $ fips <chr> "01001", "01001", "01001", "01001", "01001", "01001", "01001", "…
## $ year <dbl> 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905…
## $ temp <dbl> 62.63333, 65.34167, 65.15000, 63.81667, 63.92500, 64.17500, 62.2…
## $ tempc <dbl> 17.01852, 18.52315, 18.41667, 17.67593, 17.73611, 17.87500, 16.8…glimpse(tempChangeState)## Rows: 48
## Columns: 10
## $ fips <chr> "01", "04", "05", "06", "08", "09", "10", "12", "13…
## $ Fall <dbl> -0.19566843, 1.20395062, -0.04253968, 1.57092063, 1…
## $ Spring <dbl> -0.1058624, 1.3844797, 0.2663986, 1.4492416, 1.4369…
## $ Summer <dbl> -0.32500882, 1.27445503, 0.05859612, 1.47833510, 1.…
## $ Winter <dbl> 0.4585256, 1.3883880, 0.5322469, 1.4124303, 1.83875…
## $ max_warming_season <chr> "Winter", "Winter", "Winter", "Fall", "Winter", "Wi…
## $ Annual <dbl> -0.03504762, 1.31988007, 0.21407407, 1.48056085, 1.…
## $ STUSAB <chr> "AL", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA…
## $ STATE_NAME <chr> "Alabama", "Arizona", "Arkansas", "California", "Co…
## $ STATENS <chr> "01779775", "01779777", "00068085", "01779778", "01…glimpse(tempChangeCounty)## Rows: 3,107
## Columns: 9
## $ fips <chr> "01001", "01003", "01005", "01007", "01009", "01011…
## $ Fall <dbl> -0.248564374, 0.049693122, 0.179485009, -0.39816578…
## $ Spring <dbl> -0.073735450, 0.060035273, 0.127492063, -0.21007407…
## $ Summer <dbl> -0.307132275, -0.007407407, -0.061220459, -0.576084…
## $ Winter <dbl> 0.2700388, 0.4445855, 0.8911323, 0.5307937, 0.73578…
## $ max_warming_season <chr> "Winter", "Winter", "Winter", "Winter", "Winter", "…
## $ Annual <dbl> -0.079968254, 0.142994709, 0.300250441, -0.15266666…
## $ CTYNAME <chr> "Autauga County", "Baldwin County", "Barbour County…
## $ STNAME <chr> "Alabama", "Alabama", "Alabama", "Alabama", "Alabam…skim(tempState)
skim(tempCounty)
skim(tempChangeState)
skim(tempChangeCounty)There are no missing values
line chart
tempChangeState %>% select(fips, STATE_NAME)%>% right_join(tempState)%>% filter(STATE_NAME %in% c("Michigan", "Minnesota")) %>% ggplot(aes(x = year, y = temp, color = STATE_NAME)) +
geom_line() +
scale_color_colorblind() +
labs(x = "Year", y = "Temperature (F)", title = "Temerature of Michigan and Minnesota, 1895-2019", caption = "Data source: The Washington Post and the NOAA nCLimDiv and nClimGrid data sets", color = "") +
theme_bw() +
theme(legend.position = "bottom")## Joining, by = "fips"
pivoting to long format
tempChangeStateLong <-tempChangeState %>%
pivot_longer(cols = c(Fall:Winter, Annual),
names_to = "Period",
values_to = "Change")
tempChangeCountyLong <-tempChangeCounty %>%
pivot_longer(cols = c(Fall:Winter, Annual),
names_to = "Period",
values_to = "Change")tempChangeCountyLong %>% slice_max(Change, n =10)## # A tibble: 10 × 6
## fips max_warming_season CTYNAME STNAME Period Change
## <chr> <chr> <chr> <chr> <chr> <dbl>
## 1 27135 Winter Roseau County Minnesota Winter 3.74
## 2 27069 Winter Kittson County Minnesota Winter 3.65
## 3 38015 Winter Burleigh County North Dakota Winter 3.60
## 4 38041 Winter Hettinger County North Dakota Winter 3.56
## 5 27061 Winter Itasca County Minnesota Winter 3.54
## 6 38009 Winter Bottineau County North Dakota Winter 3.54
## 7 38105 Winter Williams County North Dakota Winter 3.54
## 8 38079 Winter Rolette County North Dakota Winter 3.53
## 9 38053 Winter McKenzie County North Dakota Winter 3.52
## 10 38083 Winter Sheridan County North Dakota Winter 3.52bot plot
tempChangeStateLong %>% filter(Period != "Annual") %>% ggplot(aes(x = fct_relevel(Period, "Fall", "Winter", "Spring", "Summer"), y = Change)) +
geom_boxplot(fill = "dodgerblue") +
labs(title = "State-level temperature changes",
subtitle = "The lower 48 continuous United States, 1895-2019", x = "", y = "Temperature change (f)", caption = "Data Source: The Washington Post and the NOAA nClimDiv and nClimGrid data sets", color = "") +
theme_bw()
## pivoting data to a wider format
data(us_rent_income, package = "tidyr")
glimpse(us_rent_income)## Rows: 104
## Columns: 5
## $ GEOID <chr> "01", "01", "02", "02", "04", "04", "05", "05", "06", "06", "…
## $ NAME <chr> "Alabama", "Alabama", "Alaska", "Alaska", "Arizona", "Arizona…
## $ variable <chr> "income", "rent", "income", "rent", "income", "rent", "income…
## $ estimate <dbl> 24476, 747, 32940, 1200, 27517, 972, 23789, 709, 29454, 1358,…
## $ moe <dbl> 136, 3, 508, 13, 148, 4, 165, 5, 109, 3, 109, 5, 195, 5, 247,…us_rent_income_wide <- us_rent_income %>%pivot_wider(id_cols = GEOID:NAME, names_from = variable, values_from = c(estimate, moe))##bar plot
ratios <- us_rent_income_wide %>% mutate(rent_income_ratio = estimate_rent / estimate_income)
ratios %>% slice_min(rent_income_ratio, n = 10) %>%
bind_rows(ratios %>% slice_max(rent_income_ratio, n =10)) %>% ggplot(aes(x = fct_reorder(NAME, rent_income_ratio),
y = rent_income_ratio)) +
geom_col(fill = "dodgerblue", color = "black") +
labs(title = "Rent to income ratio, Inited States, 2017",
x = "",
y = "Median rent to median income ratio",
caption = "Data source: The tidycensus R package & the american Cummunity Survey") +
coord_flip() +
theme_bw()