如何从 pandas 数据框中的字符串项中删除数字 [英] How to remove numbers from string terms in a pandas dataframe

问题描述

我有一个类似于以下内容的数据框:

I have a data frame similar to the one below:

Name    Volume  Value
May21   23      21321
James   12      12311
Adi22   11      4435
Hello   34      32454
Girl90  56      654654

我希望输出采用以下格式:

I want the output to be in the format:

Name    Volume  Value
May     23      21321
James   12      12311
Adi     11      4435
Hello   34      32454
Girl    56      654654

要从名称"列中删除所有数字.

Want to remove all the numbers from the Name column.

我最近来的是在单元格级别使用以下代码进行操作:

Closest I have come is doing it at a cell level with the following code:

result = ''.join([i for i in df['Name'][1] if not i.isdigit()])

任何想法如何在系列/数据框架级别上以更好的方式进行操作.

Any idea how to do it in a better way at the series/dataframe level.

推荐答案

您可以应用

You can apply str.replace to the Name column in combination with regular expressions:

import pandas as pd

# Example DataFrame
df = pd.DataFrame.from_dict({'Name'  : ['May21', 'James', 'Adi22', 'Hello', 'Girl90'],
                             'Volume': [23, 12, 11, 34, 56],
                             'Value' : [21321, 12311, 4435, 32454, 654654]})

df['Name'] = df['Name'].str.replace('\d+', '')

print(df)

输出:

    Name   Value  Volume
0    May   21321      23
1  James   12311      12
2    Adi    4435      11
3  Hello   32454      34
4   Girl  654654      56

在正则表达式中，\d代表任何数字"，而+代表一个或多个".

In the regular expression \d stands for "any digit" and + stands for "one or more".

因此，str.replace('\d+', '')的意思是:将字符串中所有出现的数字全部替换为空".

Thus, str.replace('\d+', '') means: "Replace all occurring digits in the strings with nothing".

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