如何将 pandas 列的值设置为列表 [英] How to set the value of a pandas column as list

问题描述

我想将pandas列的值设置为字符串列表.但是，我这样做的努力没有成功，因为熊猫将列值视为可迭代的，并且得到了:ValueError: Must have equal len keys and value when setting with an iterable.

I want to set the value of a pandas column as a list of strings. However, my efforts to do so didn't succeed because pandas take the column value as an iterable and I get a: ValueError: Must have equal len keys and value when setting with an iterable.

这是MWE

>> df = pd.DataFrame({'col1': [1, 2, 3], 'col2': [4, 5, 6]})
>> df
col1    col2
0   1   4
1   2   5
2   3   6

>> df['new_col'] = None
>> df.loc[df.col1 == 1, 'new_col'] = ['a', 'b']
ValueError: Must have equal len keys and value when setting with an iterable

我试图使用df.new_col = df.new_col.astype(list)将dtype设置为list，但这也不起作用.

I tried to set the dtype as list using df.new_col = df.new_col.astype(list) and that didn't work either.

我想知道什么是正确的方法.

I am wondering what would be the correct approach here.

编辑

此处提供的答案:使用at的Python熊猫将列表插入单元格对我也不起作用.

The answer provided here: Python pandas insert list into a cell using at didn't work for me either.

推荐答案

不容易，一种可行的解决方案是创建助手Series:

Not easy, one possible solution is create helper Series:

df.loc[df.col1 == 1, 'new_col'] = pd.Series([['a', 'b']] * len(df))
print (df)
   col1  col2 new_col
0     1     4  [a, b]
1     2     5     NaN
2     3     6     NaN

另一种解决方案，如果也需要将缺失值设置为空列表，则使用列表理解:

Another solution, if need set missing values to empty list too is use list comprehension:

#df['new_col'] = [['a', 'b'] if x == 1 else np.nan for x in df['col1']]

df['new_col'] = [['a', 'b'] if x == 1 else [] for x in df['col1']]
print (df)
   col1  col2 new_col
0     1     4  [a, b]
1     2     5      []
2     3     6      []

但是随后，您将失去使用连续内存块中保存的NumPy数组的矢量化功能.

But then you lose the vectorised functionality which goes with using NumPy arrays held in contiguous memory blocks.

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