Question

DF1

Pet                            
Dog-Ralph                     
Cat                                  
2016-11-03 00:00:00

我有上面的数据框，我想转向2016-11-03 00：00：00＆＃39;值为NaN值。由于它是唯一包含冒号的值，如何将该值转换为NaN，如下所示：

感谢帮助！

Answer 1

import pandas as pd
import numpy as np

data = [{'name': 'Pet'},{'name':'Dog-Ralph'},{'name':'Cat'},{'name':'2016-11-03 00:00:00'}]

df = pd.DataFrame.from_dict(data, orient='columns')

df

输出：

    name
0   Pet
1   Dog-Ralph
2   Cat
3   2016-11-03 00:00:00

使用np.where更快地查找和替换：Read more

df['name'] = np.where(df['name'].str.contains(":"), np.nan, df['name'])

df

输出：

    name
0   Pet
1   Dog-Ralph
2   Cat
3   NaN

请参阅np.where效果详情：Why is np.where faster than pd.apply

Answer 2

你可以试试这个：

df

#   Pet
#0  Dog-Ralph
#1  Cat
#2  2016-11-03 00:00:00

import numpy as np
df[df["Pet"].notnull() & df['Pet'].str.contains(":")] = np.nan
# replace any non-nan string with `colon` with np.nan    

df
#   Pet
#0  Dog-Ralph
#1  Cat
#2  NaN

或者，如果您只需要替换Pet列：

df.loc[df["Pet"].notnull() & df["Pet"].str.contains(":"), "Pet"] = np.nan

np.nan如果包含字符python

2 个答案: