## 1. Instalar librerias

#install.packages("DataExplorer")
library("DataExplorer")
#install.packages("nycflights13")
library(nycflights13)
flights <- flights
weather <- weather
planes <- planes
airports <- airports
airlines <- airlines

2. crear reporte

#create_report(flights)

3. crear una grafica en especial

introduce(flights)
## # A tibble: 1 × 9
##     rows columns discrete_columns continuous_columns all_missing_columns
##    <int>   <int>            <int>              <int>               <int>
## 1 336776      19                5                 14                   0
## # ℹ 4 more variables: total_missing_values <int>, complete_rows <int>,
## #   total_observations <int>, memory_usage <dbl>
plot_intro(flights)

#plot_boxplot(flights)
plot_missing(flights)

plot_histogram(flights)

plot_bar(flights)
## 3 columns ignored with more than 50 categories.
## tailnum: 4044 categories
## dest: 105 categories
## time_hour: 6936 categories

plot_correlation(flights)
## 3 features with more than 20 categories ignored!
## tailnum: 4044 categories
## dest: 105 categories
## time_hour: 6936 categories
## Warning in cor(x = structure(list(year = c(2013L, 2013L, 2013L, 2013L, 2013L, :
## the standard deviation is zero

conclusion

This 3,000-flight figure is just the tip of the iceberg. Here’s a deeper dive into the daily departures from each airport: JFK: The king of international arrivals, JFK sees a constant stream of long-haul flights whisking passengers across continents.