Plot

図の作成

#install.packages( "datarium" )

library( datarium )

job = jobsatisfaction
mkt = marketing

job = as.data.frame( jobsatisfaction )
str(job)

## 'data.frame':    58 obs. of  4 variables:
##  $ id             : Factor w/ 58 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $ gender         : Factor w/ 2 levels "male","female": 1 1 1 1 1 1 1 1 1 1 ...
##  $ education_level: Factor w/ 3 levels "school","college",..: 1 1 1 1 1 1 1 1 1 2 ...
##  $ score          : num  5.51 5.65 5.07 5.51 5.94 5.8 5.22 5.36 4.78 6.01 ...

graphics による作図

dat = c( 1, 2, 4, 8, 16, 32 )

plot ( dat )

ヒストグラム

hist() 関数を使うことでヒストグラムが作成できます。 breaks を指定することでビンの数を変更できます。

hist(
  
  mkt$sales,
  main = "Sales",
  xlab = "Bin",
  col = "#2792b3", # 斜線の色
  density = 30,    # 斜線の密度
  angle = 30, # 斜線の角度
  border = "gray100", # 棒の枠線の色
  labels = TRUE, # 棒の高さの値を表示するかとか
  ylim = c( 0, 80 ),
  cex.main = 1.5, 
  cex.lab  = 1.5,
  cex.axis = 1.5
  
)

## ggplot2 パッケージによる作図

#install.packages( "ggplot2" ) 
#install.packages( "cowplot" )
#install.packages( "RColorBrewer" )

library( ggplot2 )

library( Hmisc )

##  要求されたパッケージ lattice をロード中です

##  要求されたパッケージ survival をロード中です

##  要求されたパッケージ Formula をロード中です

## 
##  次のパッケージを付け加えます: 'Hmisc'

##  以下のオブジェクトは 'package:base' からマスクされています:
## 
##     format.pval, units

library( cowplot )
library( RColorBrewer )

棒のグラフ

最小限の要素のみ 1要因の場合

  ggplot( 
    job, 
    aes( x = education_level, y = score) ) +
    stat_summary( fun = "mean", geom = "bar" 
    )

2要因の場合

# 集合棒グラフ
ggplot( job, aes( x = education_level, y = score, fill = gender ) ) +
  stat_summary( fun = "mean", geom = "bar", position = position_dodge() )

# 積み上げ棒グラフ
ggplot( job, aes( x = education_level, y = score, fill = gender ) ) +
  stat_summary( fun = "mean", geom = "bar", position = position_stack() )

装飾を加えた例

1 要因の場合

# 色分け
ggplot( job, aes( x = education_level, y = score, fill = education_level ) ) +
  stat_summary( fun = "mean", geom = "bar" )

# エラーバーを追加
ggplot( job, aes( x = education_level, y = score, fill = education_level ) ) +
  stat_summary( fun.y = "mean", geom = "bar" ) +
  stat_summary( fun.data = mean_cl_normal, geom = "errorbar",
                alpha = 0.8, size = 1, width = 0.1 )

## Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
## ℹ Please use the `fun` argument instead.

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.

# 凡例を消す、棒の枠線を追加
ggplot( job, aes( x = education_level, y = score, fill = education_level ) ) +
  stat_summary( fun.y = "mean", geom = "bar", color = "black" ) +
  theme( legend.position = "none" )

2 要因の場合

# 棒だけ

ggplot( job, aes( x = education_level, y = score, fill = gender ) ) +
  stat_summary( fun = "mean", geom = "bar", position = position_dodge() ) 

# エラーバーを追加
ggplot( job, aes( x = education_level, y = score, fill = education_level ) ) +
  stat_summary( fun.y = "mean", geom = "bar" ) +
  stat_summary( fun.data = mean_cl_normal, geom = "errorbar",
                alpha = 0.8, size = 1, width = 0.1 )

# 色を変更
ggplot( job, aes( x = education_level, y = score, fill = gender ) ) +
    stat_summary( fun.y = "mean", geom = "bar", position = position_dodge() ) +
    stat_summary( fun.data = mean_cl_normal, geom = "errorbar", alpha = 0.8, size = 1,
        width = 0.1, position = position_dodge( width = .9 ) ) +
    scale_fill_manual( values = c( "#5B84B1FF", "#FC766AFF" ) )

発表用

library( cowplot )
library( RColorBrewer )

ggplot( job, aes( x = education_level, y = score, fill = gender ) ) +
    stat_summary( fun.y = "mean", geom = "bar", position = position_dodge() ) +
    stat_summary( fun.data = mean_cl_normal, geom = "errorbar",
        alpha = 0.7, size = 1, width = 0.2, position = position_dodge( width = 0.9 ) ) + 
    scale_y_continuous( limits = c( 0, 12 ), breaks = 0:4 * 3, expand = c( 0, 0 ) ) +
    theme_cowplot( 26 ) +
    scale_fill_manual( values = c( "#5B84B1FF", "#FC766AFF" ) ) +
    xlab( "Education level" ) +
    ylab( "Score" )