当列名是整数时，按列号索引pandas DataFrame [英] Index pandas DataFrame by column numbers, when column names are integers
问题描述
我正在尝试仅保留DataFrame的某些列，并且当列名是字符串时，它可以很好地工作:
I am trying to keep just certain columns of a DataFrame, and it works fine when column names are strings:
In [2]: import numpy as np
In [3]: import pandas as pd
In [4]: a = np.arange(35).reshape(5,7)
In [5]: df = pd.DataFrame(a, ['x', 'y', 'u', 'z', 'w'], ['a', 'b', 'c', 'd', 'e', 'f', 'g'])
In [6]: df
Out[6]:
a b c d e f g
x 0 1 2 3 4 5 6
y 7 8 9 10 11 12 13
u 14 15 16 17 18 19 20
z 21 22 23 24 25 26 27
w 28 29 30 31 32 33 34
[5 rows x 7 columns]
In [7]: df[[1,3]] #No problem
Out[7]:
b d
x 1 3
y 8 10
u 15 17
z 22 24
w 29 31
但是，当列名是整数时，出现一个关键错误:
However, when column names are integers, I am getting a key error:
In [8]: df = pd.DataFrame(a, ['x', 'y', 'u', 'z', 'w'], range(10, 17))
In [9]: df
Out[9]:
10 11 12 13 14 15 16
x 0 1 2 3 4 5 6
y 7 8 9 10 11 12 13
u 14 15 16 17 18 19 20
z 21 22 23 24 25 26 27
w 28 29 30 31 32 33 34
[5 rows x 7 columns]
In [10]: df[[1,3]]
结果:
KeyError: '[1 3] not in index'
我明白了为什么熊猫不允许这样做->避免在按列名和列号建立索引之间混淆.但是，有没有办法告诉熊猫我要按列号索引?当然，一种解决方案是将列名转换为字符串，但是我想知道是否有更好的解决方案.
I can see why pandas does not allow that -> to avoid mix up between indexing by column names and column numbers. However, is there a way to tell pandas that I want to index by column numbers? Of course, one solution is to convert column names to strings, but I am wondering if there is a better solution.
推荐答案
This is exactly the purpose of iloc, see here
In [37]: df
Out[37]:
10 11 12 13 14 15 16
x 0 1 2 3 4 5 6
y 7 8 9 10 11 12 13
u 14 15 16 17 18 19 20
z 21 22 23 24 25 26 27
w 28 29 30 31 32 33 34
In [38]: df.iloc[:,[1,3]]
Out[38]:
11 13
x 1 3
y 8 10
u 15 17
z 22 24
w 29 31
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