How to Extract Column Names Containing a Specified String in Dataframes?

Extract Column Names Containing a Specified String

In dataframes, accessing columns by specific names can be crucial. This question addresses the scenario where one needs to identify a column whose name contains a specific string, even if it's not an exact match. The example provided is searching for 'spike' in column names like 'spike-2', 'hey spike', and 'spiked-in'.

Solution:

To achieve this, a straightforward approach involves iterating over the DataFrame's columns:

<code class="python">for col in df.columns:
    if 'spike' in col:
        # Do something with the column name</code>

In this solution, each column name is inspected to check if it contains the target string. If a match is found, the column name can be stored in a variable for further use.

Another option is to utilize list comprehension and filtering to create a new dataframe with only the matching columns:

<code class="python">spike_cols = [col for col in df.columns if 'spike' in col]
df2 = df.filter(regex='spike')</code>

The first line generates a list of column names that contain 'spike', while the second line filters the dataframe to include only those columns.

By leveraging these techniques, you can efficiently identify and access columns whose names contain a specific string, broadening your analytical capabilities.

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