在 pandas 数据帧中计算某些词的出现次数 [英] Count occurrences of certain words in pandas dataframe

问题描述

我想计算一个数据帧中某些字的出现次数。我知道使用str.contains

I want to count number of occurrences of certain words in a data frame. I know using "str.contains"

a = df2[df2['col1'].str.contains("sample")].groupby('col2').size()
n = a.apply(lambda x: 1).sum()

目前我正在使用上述代码。有没有一种匹配正则表达式并获得事件计数的方法？在我的情况下，我有一个大数据框，我想匹配大约100个字符串。

Currently I'm using the above code. Is there a method to match regular expression and get the count of occurrences? In my case I have a large dataframe and I want to match around 100 strings.

推荐答案

str .contains 方法接受正则表达式：

The str.contains method accepts a regular expression:

Definition: df.words.str.contains(self, pat, case=True, flags=0, na=nan)
Docstring:
Check whether given pattern is contained in each string in the array

Parameters
----------
pat : string
    Character sequence or regular expression
case : boolean, default True
    If True, case sensitive
flags : int, default 0 (no flags)
    re module flags, e.g. re.IGNORECASE
na : default NaN, fill value for missing values.

例如：

In [11]: df = pd.DataFrame(['hello', 'world'], columns=['words'])

In [12]: df
Out[12]:
   words
0  hello
1  world

In [13]: df.words.str.contains(r'[hw]')
Out[13]:
0    True
1    True
Name: words, dtype: bool

In [14]: df.words.str.contains(r'he|wo')
Out[14]:
0    True
1    True
Name: words, dtype: bool

要计算出现的结果，您可以将此布尔值系列：

To count the occurences you can just sum this boolean Series:

In [15]: df.words.str.contains(r'he|wo').sum()
Out[15]: 2

In [16]: df.words.str.contains(r'he').sum()
Out[16]: 1

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