## ----setup-init, include=FALSE------------------------------------------------ library(knitr) source("scripts/image_functions.R") ## ----wrangling-load-packages, message=FALSE----------------------------------- library(dplyr) library(ggplot2) library(nycflights23) ## ----wrangling-filter-envoy, eval=FALSE--------------------------------------- # envoy_flights <- flights |> # filter(carrier == "MQ") ## ----wrangling-view-phoenix_flights, eval=FALSE------------------------------- # phoenix_flights <- flights |> # filter(dest == "PHX") # View(phoenix_flights) ## ----wrangling-view-btv_sea_flights_fall, eval=FALSE-------------------------- # btv_sea_flights_fall <- flights |> # filter(origin == "JFK" & (dest == "BTV" | dest == "SEA") & month >= 10) # View(btv_sea_flights_fall) ## ----wrangling-assign-btv_sea_flights_fa, eval=FALSE-------------------------- # btv_sea_flights_fall <- flights |> # filter(origin == "JFK", (dest == "BTV" | dest == "SEA"), month >= 10) # View(btv_sea_flights_fall) ## ----wrangling-view-not_BTV_SEA, eval=FALSE----------------------------------- # not_BTV_SEA <- flights |> # filter(!(dest == "BTV" | dest == "SEA")) # View(not_BTV_SEA) ## ----wrangling-filter, eval=FALSE--------------------------------------------- # flights |> filter(!dest == "BTV" | dest == "SEA") ## ----wrangling-create-many_airports, eval=FALSE------------------------------- # many_airports <- flights |> # filter(dest == "SEA" | dest == "SFO" | dest == "PHX" | # dest == "BTV" | dest == "BDL") ## ----wrangling-view-many_airports, eval=FALSE--------------------------------- # many_airports <- flights |> # filter(dest %in% c("SEA", "SFO", "PHX", "BTV", "BDL")) # View(many_airports) ## ----wrangling-conditional-text, echo=FALSE, results="asis"------------------- if(!is_latex_output()) cat("See [Appendix A online](https://moderndive.com/v2/appendixa) for a glossary of such summary statistics.") ## ----wrangling-mean-and-sd---------------------------------------------------- summary_windspeed <- weather |> summarize(mean = mean(wind_speed), std_dev = sd(wind_speed)) summary_windspeed ## ----wrangling-mean-sd-wind--------------------------------------------------- summary_windspeed <- weather |> summarize(mean = mean(wind_speed, na.rm = TRUE), std_dev = sd(wind_speed, na.rm = TRUE)) summary_windspeed ## ----wrangling-assign-summary_windspeed, eval=FALSE--------------------------- # summary_windspeed <- weather |> # summarize(mean = mean(wind_speed, na.rm = TRUE)) |> # summarize(std_dev = sd(wind_speed, na.rm = TRUE)) ## ----wrangling-mean-sd-temp--------------------------------------------------- summary_temp <- weather |> summarize(mean = mean(wind_speed, na.rm = TRUE), std_dev = sd(wind_speed, na.rm = TRUE)) summary_temp ## ----wrangling-summary-by-month----------------------------------------------- summary_monthly_windspeed <- weather |> group_by(month) |> summarize(mean = mean(wind_speed, na.rm = TRUE), std_dev = sd(wind_speed, na.rm = TRUE)) summary_monthly_windspeed ## ----wrangling-show-diamonds-------------------------------------------------- diamonds ## ----wrangling-demo-code------------------------------------------------------ diamonds |> group_by(cut) ## ----wrangling-grouped-summary------------------------------------------------ diamonds |> group_by(cut) |> summarize(avg_price = mean(price)) ## ----wrangling-ungroup-data--------------------------------------------------- diamonds |> group_by(cut) |> ungroup() ## ----wrangling-summary-by-origin---------------------------------------------- by_origin <- flights |> group_by(origin) |> summarize(count = n()) by_origin ## ----wrangling-assign-by_origin_monthly--------------------------------------- by_origin_monthly <- flights |> group_by(origin, month) |> summarize(count = n()) ## ----wrangling-v26------------------------------------------------------------ by_origin_monthly ## ----wrangling-count-by-origin------------------------------------------------ by_origin_monthly_incorrect <- flights |> group_by(origin) |> group_by(month) |> summarize(count = n()) by_origin_monthly_incorrect ## ----wrangling-create-weather, eval=TRUE-------------------------------------- weather <- weather |> mutate(temp_in_C = (temp - 32) / 1.8) ## ----wrangling-summary-by-month-v4-------------------------------------------- summary_monthly_temp <- weather |> group_by(month) |> summarize(mean_temp_in_F = mean(temp, na.rm = TRUE), mean_temp_in_C = mean(temp_in_C, na.rm = TRUE)) summary_monthly_temp ## ----wrangling-mutate-gain---------------------------------------------------- flights <- flights |> mutate(gain = dep_delay - arr_delay) ## ----wrangling-mean-sd-narm--------------------------------------------------- gain_summary <- flights |> summarize( min = min(gain, na.rm = TRUE), q1 = quantile(gain, 0.25, na.rm = TRUE), median = quantile(gain, 0.5, na.rm = TRUE), q3 = quantile(gain, 0.75, na.rm = TRUE), max = max(gain, na.rm = TRUE), mean = mean(gain, na.rm = TRUE), sd = sd(gain, na.rm = TRUE), missing = sum(is.na(gain)) ) gain_summary ## ----fig-gain-hist, fig.alt="Right-skewed histogram of the gain variable (departure delay minus arrival delay), centered near zero with a long right tail and a few extreme positive values.", fig.cap="Histogram of gain variable.", message=FALSE, fig.height=ifelse(knitr::is_latex_output(), 3, 4)---- ggplot(data = flights, mapping = aes(x = gain)) + geom_histogram(color = "white", bins = 20) ## ----wrangling-mutate-gain-demo----------------------------------------------- flights <- flights |> mutate( gain = dep_delay - arr_delay, hours = air_time / 60, gain_per_hour = gain / hours ) ## ----wrangling-count-by-dest-------------------------------------------------- freq_dest <- flights |> group_by(dest) |> summarize(num_flights = n()) freq_dest ## ----wrangling-arrange-------------------------------------------------------- freq_dest |> arrange(num_flights) ## ----wrangling-arrange-desc--------------------------------------------------- freq_dest |> arrange(desc(num_flights)) ## ----wrangling-view-airlines, eval=FALSE-------------------------------------- # View(airlines) ## ----wrangling-view-flights, eval=FALSE--------------------------------------- # flights_joined <- flights |> # inner_join(airlines, by = "carrier") # View(flights) # View(flights_joined) ## ----wrangling-view-airports, eval=FALSE-------------------------------------- # View(airports) ## ----wrangling-view-flights_with_airport, eval=FALSE-------------------------- # flights_with_airport_names <- flights |> # inner_join(airports, by = c("dest" = "faa")) # View(flights_with_airport_names) ## ----wrangling-count-by-dest2------------------------------------------------- named_dests <- flights |> group_by(dest) |> summarize(num_flights = n()) |> arrange(desc(num_flights)) |> inner_join(airports, by = c("dest" = "faa")) |> rename(airport_name = name) named_dests ## ----wrangling-view-flights_weather_join, eval=FALSE-------------------------- # flights_weather_joined <- flights |> # inner_join(weather, by = c("year", "month", "day", "hour", "origin")) # View(flights_weather_joined) ## ----wrangling-view-joined_flights, eval=FALSE-------------------------------- # joined_flights <- flights |> # inner_join(airlines, by = "carrier") # View(joined_flights) ## ----wrangling-glimpse-flights, eval=FALSE------------------------------------ # glimpse(flights) ## ----wrangling-select-vars, eval=FALSE---------------------------------------- # flights |> # select(carrier, flight) ## ----wrangling-create-flights_no_year, eval=FALSE----------------------------- # flights_no_year <- flights |> select(-year) ## ----wrangling-create-flight_arr_times, eval=FALSE---------------------------- # flight_arr_times <- flights |> select(month:day, arr_time:sched_arr_time) # flight_arr_times ## ----wrangling-select-vars-alt, eval=FALSE------------------------------------ # flights |> select(starts_with("a")) # flights |> select(ends_with("delay")) # flights |> select(contains("time")) ## ----wrangling-glimpse-flights_reorder, eval=FALSE---------------------------- # flights_reorder <- flights |> # select(year, month, day, hour, minute, time_hour, everything()) # glimpse(flights_reorder) ## ----wrangling-glimpse-flights_relocate, eval=FALSE--------------------------- # flights_relocate <- flights |> # relocate(hour, minute, time_hour, .after = day) # glimpse(flights_relocate) ## ----wrangling-glimpse-flights_time_new, eval=FALSE--------------------------- # flights_time_new <- flights |> # select(dep_time, arr_time) |> # rename(departure_time = dep_time, arrival_time = arr_time) # glimpse(flights_time_new) ## ----wrangling-demo-code-v2, eval=FALSE--------------------------------------- # named_dests |> top_n(n = 10, wt = num_flights) ## ----wrangling-demo-code-v2-dup1, eval=FALSE---------------------------------- # named_dests |> # top_n(n = 10, wt = num_flights) |> # arrange(desc(num_flights)) ## ----------------------------------------------------------------------------- #| label: ch3-exercises #| results: asis #| echo: false #| message: false source(if (file.exists("scripts/exercise_helpers.R")) "scripts/exercise_helpers.R" else "../scripts/exercise_helpers.R") cat(render_chapter_exercises(3)) ## ----wrangling-conditional-text-v2, echo=FALSE, results="asis"---------------- if(!is_latex_output()) cat("In the online [Appendix C](https://moderndive.com/v2/appendixc.html), we provide a page of data wrangling 'tips and tricks' consisting of the most common data wrangling questions we've encountered in student projects (shout out to [Dr. Jenny Smetzer](https://www.scsparkscience.org/fellow/jennifer-smetzer/) for her work setting this up!): * Dealing with missing values * Reordering bars in a barplot * Showing money on an axis * Changing values inside cells * Converting a numerical variable to a categorical one * Computing proportions * Dealing with %, commas, and dollar signs However, to provide a tips and tricks page covering all possible data wrangling questions would be too long to be useful!")