从csv文件中读取列的多索引

Question

我有一个.csv文件,如下所示:

Male, Male, Male, Female, Female
R, R, L, R, R
.86, .67, .88, .78, .81

我想把它读成df,所以我有:

    Male        Female
    R       L   R
0   .86 .67 .88 .78 .81

我做了:

df = pd.read_csv('file.csv', header=[0,1])

但headers不削减它.结果如何

Empty DataFrame
Columns: [(Male, R), (Male, R), (Male, L), (Female, R), (Female, R)]
Index: []

然而,标题上的文档说:

(...)Can be a list of integers that specify row
locations for a multi-index on the columns E.g. [0,1,3]

我究竟做错了什么？我怎么可能让它工作？

Answer 1

我认为问题是你有重复的列:两个(女性,R).

不确定它是否是错误或重复的列是不可接受的.这是给你的解决方法:

首先用tupleize_cols = True读取csv

In [61]: df = pd.read_csv('test.csv', header=[0, 1], skipinitialspace=True, tupleize_cols=True)

In [62]: df
Out[62]: 
   (Male, R)  (Male, R)  (Male, L)  (Female, R)  (Female, R)
0       0.67       0.67       0.88         0.81         0.81

[1 rows x 5 columns]

然后将列的类型从Index转换为MultiIndex

In [63]: df.columns = pd.MultiIndex.from_tuples(df.columns)

In [64]: df
Out[64]: 
   Male              Female      
      R     R     L       R     R
0  0.67  0.67  0.88    0.81  0.81

[1 rows x 5 columns]

Answer 2

从熊猫的0.21版本开始，默认情况下会创建MultiIndexes，因此df = pd.read_csv('file.csv', header=[0,1])应该做。