Find column whose name contains a specific string

I have a dataframe with column names, and I want to find the one that contains a certain string, but does not exactly match it. I'm searching for 'spike' in column names like 'spike-2', 'hey spike', 'spiked-in' (the 'spike' part is always continuous).

I want the column name to be returned as a string or a variable, so I access the column later with df['name'] or df[name] as normal. I've tried to find ways to do this, to no avail. Any tips?

Just iterate over DataFrame.columns, now this is an example in which you will end up with a list of column names that match:

    import pandas as pd

    data = {'spike-2': [1,2,3], 'hey spke': [4,5,6], 'spiked-in': [7,8,9], 'no': [10,11,12]}
    df = pd.DataFrame(data)

    spike_cols = [col for col in df.columns if 'spike' in col]
    print(list(df.columns))
    print(spike_cols)

Output:

    ['hey spke', 'no', 'spike-2', 'spiked-in']
    ['spike-2', 'spiked-in']

Explanation:

  1. df.columns returns a list of column names
  2. [col for col in df.columns if 'spike' in col] iterates over the list df.columns with the variable col and adds it to the resulting list if col contains 'spike'. This syntax is list comprehension.

If you only want the resulting data set with the columns that match you can do this:

    df2 = df.filter(regex='spike')
    print(df2)

Output:

       spike-2  spiked-in
    0        1          7
    1        2          8
    2        3          9

From: stackoverflow.com/q/21285380

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