将 pandas 数据框中的列从 int 转换为 string

2022-01-14 00:00:00 python pandas dataframe string int

问题描述

我在 pandas 中有一个混合了 int 和 str 数据列的数据框.我想首先连接数据框中的列.为此，我必须将 int 列转换为 str.我尝试过如下操作:

I have a dataframe in pandas with mixed int and str data columns. I want to concatenate first the columns within the dataframe. To do that I have to convert an int column to str. I've tried to do as follows:

mtrx['X.3'] = mtrx.to_string(columns = ['X.3'])

或

mtrx['X.3'] = mtrx['X.3'].astype(str)

但在这两种情况下它都不起作用，我收到一条错误消息，提示无法连接 'str' 和 'int' 对象".连接两个 str 列效果很好.

but in both cases it's not working and I'm getting an error saying "cannot concatenate 'str' and 'int' objects". Concatenating two str columns is working perfectly fine.

解决方案

In [16]: df = DataFrame(np.arange(10).reshape(5,2),columns=list('AB'))

In [17]: df
Out[17]: 
   A  B
0  0  1
1  2  3
2  4  5
3  6  7
4  8  9

In [18]: df.dtypes
Out[18]: 
A    int64
B    int64
dtype: object

<小时>

转换一个系列

Convert a series

In [19]: df['A'].apply(str)
Out[19]: 
0    0
1    2
2    4
3    6
4    8
Name: A, dtype: object

In [20]: df['A'].apply(str)[0]
Out[20]: '0'

别忘了把结果赋值回去:

Don't forget to assign the result back:

df['A'] = df['A'].apply(str)

<小时>

转换整个帧

Convert the whole frame

In [21]: df.applymap(str)
Out[21]: 
   A  B
0  0  1
1  2  3
2  4  5
3  6  7
4  8  9

In [22]: df.applymap(str).iloc[0,0]
Out[22]: '0'


df = df.applymap(str)

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