介绍几个数据描述性统计的R包。
psych::describe()
psych::describe(iris)
## 带星号的是因子
# vars n mean sd median trimmed mad min max range skew kurtosis se
# Sepal.Length 1 150 5.84 0.83 5.80 5.81 1.04 4.3 7.9 3.6 0.31 -0.61 0.07
# Sepal.Width 2 150 3.06 0.44 3.00 3.04 0.44 2.0 4.4 2.4 0.31 0.14 0.04
# Petal.Length 3 150 3.76 1.77 4.35 3.76 1.85 1.0 6.9 5.9 -0.27 -1.42 0.14
# Petal.Width 4 150 1.20 0.76 1.30 1.18 1.04 0.1 2.5 2.4 -0.10 -1.36 0.06
# Species* 5 150 2.00 0.82 2.00 2.00 1.48 1.0 3.0 2.0 0.00 -1.52 0.07
skimr::skim()
skimr::skim(iris)
# Skim summary statistics
# n obs: 150
# n variables: 5
#
# -- Variable type:factor --------------------------------------------------------
# variable missing complete n n_unique top_counts ordered
# Species 0 150 150 3 set: 50, ver: 50, vir: 50, NA: 0 FALSE
#
# -- Variable type:numeric -------------------------------------------------------
# variable missing complete n mean sd p0 p25 p50 p75 p100 hist
# Petal.Length 0 150 150 3.76 1.77 1 1.6 4.35 5.1 6.9 ▇▁▁▂▅▅▃▁
# Petal.Width 0 150 150 1.2 0.76 0.1 0.3 1.3 1.8 2.5 ▇▁▁▅▃▃▂▂
# Sepal.Length 0 150 150 5.84 0.83 4.3 5.1 5.8 6.4 7.9 ▂▇▅▇▆▅▂▂
# Sepal.Width 0 150 150 3.06 0.44 2 2.8 3 3.3 4.4 ▁▂▅▇▃▂▁▁
summarytools::dfSummary(iris)
library(summarytools)
view(dfSummary(iris))
![](https://img.haomeiwen.com/i3289684/cde9b742d099e35f.png)
网友评论