数据['col'].values中的字符串，但数据['col']中的字符串 [英] String in data['col'].values but not in data['col']

问题描述

我已经从文件中读取了一个熊猫数据框:

I've read a Pandas dataframe from file:

df = pd.read_csv('data_here.csv')

当我尝试"str2try" in df['col2search']时，它返回False，但是当我尝试"str2try" in df['col2search'].values时，它返回True(这是本例中的期望值).

When I try "str2try" in df['col2search'] it returns False, but when I try "str2try" in df['col2search'].values, it returns True (and this is what I'd expect in this case).

我不明白为什么会有行为上的差异；我读到.values返回该列的Numpy表示形式，但是为什么"str2try" in <NDFrame representation of column>返回False?

I don't see why there would be a behavioral difference; I read that .values returns the Numpy representation of the column, but why does "str2try" in <NDFrame representation of column> return False?

谢谢！

推荐答案

Pandas系列就像一本字典. in搜索其索引(或键)，因此"str2try" in df['col2search']检查字符串是否在该系列的 index 中:

A pandas Series is like a dictionary. in searches its index (or keys) so "str2try" in df['col2search'] checks whether the string is in the index of that Series:

df = pd.DataFrame({'A': [1, 2, 3]}, index=['x', 'y', 'z'])

df
Out: 
   A
x  1
y  2
z  3

'x' in df['A']
Out: True

2 in df['A']
Out: False

'x' in df['A'].values
Out: False

2 in df['A'].values
Out: True

这是它在字典中的表现方式:

Here's how it would behave in a dictionary:

d = {'x': 1, 'y': 2, 'z': 3}

'x' in d
Out: True

2 in d
Out: False

2 in d.values()
Out: True

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