Replace whole string if it contains substring in pandas
PythonPandasPython Problem Overview
I want to replace all strings that contain a specific substring. So for example if I have this dataframe:
import pandas as pd
df = pd.DataFrame({'name': ['Bob', 'Jane', 'Alice'],
'sport': ['tennis', 'football', 'basketball']})
I could replace football with the string 'ball sport' like this:
df.replace({'sport': {'football': 'ball sport'}})
What I want though is to replace everything that contains ball (in this case football and basketball) with 'ball sport'. Something like this:
df.replace({'sport': {'[strings that contain ball]': 'ball sport'}})
Python Solutions
Solution 1 - Python
You can use str.contains to mask the rows that contain 'ball' and then overwrite with the new value:
In [71]:
df.loc[df['sport'].str.contains('ball'), 'sport'] = 'ball sport'
df
Out[71]:
name sport
0 Bob tennis
1 Jane ball sport
2 Alice ball sport
To make it case-insensitive pass `case=False:
df.loc[df['sport'].str.contains('ball', case=False), 'sport'] = 'ball sport'
Solution 2 - Python
You can use apply with a lambda. The x parameter of the lambda function will be each value in the 'sport' column:
df.sport = df.sport.apply(lambda x: 'ball sport' if 'ball' in x else x)
Solution 3 - Python
you can use str.replace
df.sport.str.replace(r'(^.*ball.*$)', 'ball sport')
0 tennis
1 ball sport
2 ball sport
Name: sport, dtype: object
reassign with
df['sport'] = df.sport.str.replace(r'(^.*ball.*$)', 'ball sport')
df
Solution 4 - Python
A different str.contains
df['support'][df.name.str.contains('ball')] = 'ball support'
Solution 5 - Python
You can use a lambda function also:
data = {"number": [1, 2, 3, 4, 5], "function": ['IT', 'IT application',
'IT digital', 'other', 'Digital'] }
df = pd.DataFrame(data)
df.function = df.function.apply(lambda x: 'IT' if 'IT' in x else x)