Table of Contents
Pandas provides a simple and efficient way to select columns containing a specific string using the str.contains() function. This function takes a string as an argument and returns a Boolean value indicating if the column contains the string. You can then use this Boolean value to select only the columns that contain the string from the dataframe. This approach allows you to quickly and easily filter down a dataframe to select only the columns containing the string that you are interested in.
You can use the following methods to select columns that contain a particular string in a pandas DataFrame:
Method 1: Select Columns that Contain One Specific String
df.filter(regex='string1')
Method 2: Select Columns that Contain One of Several Strings
df.filter(regex='string1|string2|string3')
The following examples show how to use each of these methods in practice with the following pandas DataFrame:
import pandas as pd
#create DataFrame
df = pd.DataFrame({'mavs': [10, 12, 14, 15, 19, 22, 27],
'cavs': [18, 22, 19, 14, 14, 11, 20],
'hornets': [5, 7, 7, 9, 12, 9, 14],
'spurs': [10, 12, 14, 13, 13, 19, 22],
'nets': [10, 14, 25, 22, 25, 17, 12]})
#view DataFrame
print(df)
mavs cavs hornets spurs nets
0 10 18 5 10 10
1 12 22 7 12 14
2 14 19 7 14 25
3 15 14 9 13 22
4 19 14 12 13 25
5 22 11 9 19 17
6 27 20 14 22 12
Example 1: Select Columns that Contain One Specific String
The following code shows how to use the filter() function to select only the columns that contain the string “avs” somewhere in their name:
#select columns that contain 'avs' in the name
df2 = df.filter(regex='avs')
#view DataFrame
print(df2)
mavs cavs
0 10 18
1 12 22
2 14 19
3 15 14
4 19 14
5 22 11
6 27 20
Only the columns that contain “avs” in the name are returned.
In this case, “mavs” and “cavs” are the only columns that are returned.
Example 2: Select Columns that Contain One of Several Strings
The following code shows how to use the filter() function to select only the columns that contain “avs” or “ets” somewhere in their name:
#select columns that contain 'avs' in the name
df2 = df.filter(regex='avs|ets')
#view DataFrame
print(df2)
mavs cavs hornets nets
0 10 18 5 10
1 12 22 7 14
2 14 19 7 25
3 15 14 9 22
4 19 14 12 25
5 22 11 9 17
6 27 20 14 12 Only the columns that contain “avs” or “ets” in the name are returned.
Note that the vertical bar ( | ) is the “OR” operator in pandas.