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设置pandas.DataFrame对象的列

[英]set column of pandas.DataFrame object

Ideally, I want to be able something like: 理想情况下,我希望能够实现以下功能:

cols = ['A', 'B', 'C']
df = pandas.DataFrame(index=range(5), columns=cols)
df.get_column(cols[0]) = [1, 2, 3, 4, 5]

What is the pythonic/pandonic way to do this? 什么是pythonic / pandonic方法?

Edit: I know that I can access the column 'A' by df.A , but in general I do not know what the column names are. 编辑:我知道我可以通过df.A访问列“ A”,但通常我不知道列名是什么。

好的,这特别简单。

df[cols[0]] = [1, 2, 3, 4, 5] 

You do not need to store what columns a DataFrame has separately. 您不需要存储DataFrame的哪些列。

You can find out what columns exist in a pandas DataFrame by accessing the DataFrame.columns variable. 您可以通过访问DataFrame.columns变量来找出熊猫DataFrame中存在哪些列。

To access the Series attached to a particular column, you can use the getitem method of the DataFrame [] 要访问附加到特定列的系列,可以使用DataFrame []的getitem方法

Tiny example: 小例子:

col = df.columns[0]
df[col] = [1, 2, 3, 4, 5]

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