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Contents
- 1 れ
- 2 ろ 一危 襷り鍵
- 3 一 覲, 伎壱 覲, Missing Value
- 4 Missing Value
- 5 Histogram
- 6 Density
- 7 BoxPlot
- 8 Correlation
- 9 Categorical
- 10 Automating EDA
install.packages("DataExplorer")
library(DataExplorer)
2 ろ 一危 襷り鍵 #
mydata <- iris
mydata[5:50, 3] <- NA
mydata$Species <- as.factor(mydata$Species)
head(mydata)
3 一 覲, 伎壱 覲, Missing Value #
plot_intro(mydata, title = "Automated EDA with Data Explorer")
4 Missing Value #
plot_missing(mydata)
5 Histogram #
plot_histogram(mydata)
6 Density #
plot_density(mydata)
7 BoxPlot #
plot_boxplot(mydata, by= 'Species', ncol = 2)
8 Correlation #
plot_correlation(mydata, cor_args = list( 'use' = 'complete.obs'))
plot_correlation(mydata, type = 'c', cor_args = list( 'use' = 'complete.obs'))
9 Categorical #
plot_bar(mydata$Species, maxcat = 20)
#plot_bar(mydata, maxcat = 20, parallel = TRUE) #Windows OS 讌
plot_bar(mydata, with = c("Sepal.Length"), maxcat = 20)
#plot_bar(mydata, with = c("Sepal.Length"), maxcat = 20, parallel = TRUE)
10 Automating EDA #
企蟆 覃 Data Profiling Report螳 襷れ 讌.
create_report(mydata)
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