使用方括号或点访问列有什么区别? [英] What is the difference between using squared brackets or dot to access a column?

问题描述

在以下两种情况下:

import pandas

d = {'col1': 2, 'col2': 2.5}
df = pandas.DataFrame(data=d, index=[0])

print(df['col2'])
print(df.col2)

两种方法都可以对列进行索引并产生相同的结果，那么它们之间有什么区别吗?

Both methods can be used to index on a column and yield the same result, so is there any difference between them?

推荐答案

点符号"，即 df.col2 是 属性访问，为了方便而公开.

The "dot notation", i.e. df.col2 is the attribute access that's exposed as a convenience.

您可以直接作为属性访问系列上的索引、DataFrame 上的列和面板上的项目:

You may access an index on a Series, column on a DataFrame, and an item on a Panel directly as an attribute:

df['col2'] 做同样的事情:它返回列的 pd.Series.

df['col2'] does the same: it returns a pd.Series of the column.

关于属性访问的一些注意事项:

A few caveats about attribute access:

• 你不能添加一个列(df.new_col = x 不起作用，更糟糕的是:它会悄悄地实际创建一个新属性而不是一个列 - 想想猴子-在这里打补丁)
• 如果列名中有空格或列名是整数，则此方法无效.

• you cannot add a column (df.new_col = x won't work, worse: it will silently actually create a new attribute rather than a column - think monkey-patching here)
• it won't work if you have spaces in the column name or if the column name is an integer.

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