将具有multi_index列的熊猫数据框传输到R

Question

如何将具有多个索引列的熊猫数据框传输到R？最好使用CSV文件？

import pandas as pd

df = pd.DataFrame({'foo':[1,1,2], 'baz':['a', 'c', 'b'], 'bar':[0.2, 0.6, 0.9], 'x':[4, 0.6, 0.9]})
display(df)
df = df.groupby(['foo', 'baz']).describe()
display(df)

导致：

df.to_csv("test.csv")生成以下CSV文件：

,,bar,bar,bar,bar,bar,bar,bar,bar,x,x,x,x,x,x,x,x
,,count,mean,std,min,25%,50%,75%,max,count,mean,std,min,25%,50%,75%,max
foo,baz,,,,,,,,,,,,,,,,
1,a,1.0,0.2,,0.2,0.2,0.2,0.2,0.2,1.0,4.0,,4.0,4.0,4.0,4.0,4.0
1,c,1.0,0.6,,0.6,0.6,0.6,0.6,0.6,1.0,0.6,,0.6,0.6,0.6,0.6,0.6
2,b,1.0,0.9,,0.9,0.9,0.9,0.9,0.9,1.0,0.9,,0.9,0.9,0.9,0.9,0.9

我如何保留这种层次结构？或者，如果不可能的话，至少让R自动连接名称以保留标题中的信息

Answer 1

• 合并多级名称，然后保存到csv。

# as_index=False
df = df.groupby(['foo', 'baz'], as_index=False).describe()

# combine the column names with a .
df.columns = df.columns.map('.'.join)

 foo.count  foo.mean  foo.std  foo.min  foo.25%  foo.50%  foo.75%  foo.max  bar.count  bar.mean  bar.std  bar.min  bar.25%  bar.50%  bar.75%  bar.max  x.count  x.mean  x.std  x.min  x.25%  x.50%  x.75%  x.max
       1.0       1.0      NaN      1.0      1.0      1.0      1.0      1.0        1.0       0.2      NaN      0.2      0.2      0.2      0.2      0.2      1.0     4.0    NaN    4.0    4.0    4.0    4.0    4.0
       1.0       1.0      NaN      1.0      1.0      1.0      1.0      1.0        1.0       0.6      NaN      0.6      0.6      0.6      0.6      0.6      1.0     0.6    NaN    0.6    0.6    0.6    0.6    0.6
       1.0       2.0      NaN      2.0      2.0      2.0      2.0      2.0        1.0       0.9      NaN      0.9      0.9      0.9      0.9      0.9      1.0     0.9    NaN    0.9    0.9    0.9    0.9    0.9