CODEWITHSUNDEEP
pythonpandas
Mitchell Posluns
Mitchell Posluns

Reputation: 86

Pandas filter dataframe by single condition across multiple columns

I have a dataframe with 30 columns, each cell containing a 1 or 0.

I would like to filter the dataframe for where any 1 of 4 specific columns == 1.

Right now, it would have to be chained masks like: 

df[(df['col1'] == 1) | (df['col2'] == 1) | (df['col3'] == 1) | (df['col4'] == 1)]

Is there a simpler and scalable way to do this? Something like making a list of the column names, and using slice notation to check all boolean conditions in one go?:

col_list = ['col1', 'col2', 'col3', 'col4']

df[df[col_list] == 1]

Upvotes: 1

Views: 191

Answers (1)

Aditya Lahiri
Aditya Lahiri

Reputation: 419

Try this: 

col_df=list(df) # get all the column names 
filtered_df=df[df[col_df].any(1)]

Upvotes: 2

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