How To Select All Columns That Start With "durations" Or "shape"?

How to select all columns that have header names starting with 'durations' or 'shape'? (instead of defining a long list of column names). I need to select these columns and substit

Solution 1:

You could use str methods of dataframe startwith:

df = data[data.columns[data.columns.str.startwith('durations') | data.columns.str.startwith('so')]]
df.fillna(0)

Or you could use contains method:

df = data.iloc[:, data.columns.str.contains('durations.*'|'shape.*') ]
df.fillna(0)

Solution 2:

I would use the select method:

df.select(lambda c: c.startwith('durations') or c.startswith('shape'), axis=1)

Solution 3:

Use my_dataframe.columns.values.tolist() to get the column names (based on Get list from pandas DataFrame column headers):

column_names = [x for x in data.columns.values.tolist() if x.startswith("durations") or x.startswith("shape")]

Solution 4:

A simple and easy way

data[data.filter(regex='durations|shape').columns].fillna(0)

Sample Screenshot