La librería Data Explorer es la más conocida para el análisis exploratorio. Es muy simple de usar y muy poderosa, pues ofrece como salida un informe con mucha información.
La función para crear el informe es create_report(), y para ver cada gráfica de forma individual, las funciones son:
#install.packages("DataExplorer")
library(DataExplorer)
#install.packages("nycflights13")
library(nycflights13)
El paqute nycflights13 contiene información sobre todos los vuelos que partieron desde Nueva York (EWR, JFK, y LGA) a destinos en los Estados Unidos en 2013. Fueron 336,776 vuelos en total.
Las tablas de este paquete y sus relaciones son las siguientes:
.
flights <- flights
weather <- weather
planes <- planes
airports <- airports
airlines <- airlines
df <- merge(flights, airlines, by="carrier")
df <- merge(df, planes, by="tailnum")
create_report(df)
##
##
## processing file: report.rmd
##
|
| | 0%
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|. | 2%
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|.. | 5% [global_options]
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|... | 7%
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|.... | 10% [introduce]
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|.... | 12%
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|..... | 14% [plot_intro]
|
|...... | 17%
|
|....... | 19% [data_structure]
|
|........ | 21%
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|......... | 24% [missing_profile]
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|.......... | 26%
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|........... | 29% [univariate_distribution_header]
|
|........... | 31%
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|............ | 33% [plot_histogram]
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|............. | 36%
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|.............. | 38% [plot_density]
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|............... | 40%
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|................ | 43% [plot_frequency_bar]
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|................. | 45%
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|.................. | 48% [plot_response_bar]
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|.................. | 50%
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|................... | 52% [plot_with_bar]
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|.................... | 55%
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|..................... | 57% [plot_normal_qq]
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|...................... | 60%
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|....................... | 62% [plot_response_qq]
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|........................ | 64%
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|......................... | 67% [plot_by_qq]
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|.......................... | 69%
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|.......................... | 71% [correlation_analysis]
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|........................... | 74%
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|............................ | 76% [principal_component_analysis]
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|............................. | 79%
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|.............................. | 81% [bivariate_distribution_header]
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|............................... | 83%
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|................................ | 86% [plot_response_boxplot]
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|................................. | 88%
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|................................. | 90% [plot_by_boxplot]
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|.................................. | 93%
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|................................... | 95% [plot_response_scatterplot]
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|.................................... | 98%
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|.....................................| 100% [plot_by_scatterplot]
## output file: /Users/lishdz/Desktop/6to/R/Módulo 2 /report.knit.md
## /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/pandoc +RTS -K512m -RTS '/Users/lishdz/Desktop/6to/R/Módulo 2 /report.knit.md' --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output pandocb216e05c2b4.html --lua-filter /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/rmarkdown/rmarkdown/lua/latex-div.lua --embed-resources --standalone --variable bs3=TRUE --section-divs --table-of-contents --toc-depth 6 --template /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=yeti --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /var/folders/g9/79hnblwx58vc4d8_1dwhqvwm0000gn/T//RtmpPQZ9x8/rmarkdown-strb2156dd9781.html
##
## Output created: report.html
introduce(df)
## rows columns discrete_columns continuous_columns all_missing_columns
## 1 284170 28 10 18 0
## total_missing_values complete_rows total_observations memory_usage
## 1 311768 920 7956760 50225296
plot_intro(df)
plot_boxplot(df, by="carrier")
## Warning: Removed 23255 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
## Warning: Removed 288513 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
plot_missing(df)
plot_histogram(df)
plot_correlation(df)
## 5 features with more than 20 categories ignored!
## tailnum: 3322 categories
## dest: 104 categories
## time_hour: 6934 categories
## manufacturer: 35 categories
## model: 127 categories
## Warning in cor(x = structure(list(year.x = c(2013L, 2013L, 2013L, 2013L, : the
## standard deviation is zero