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Select columns if any of their rows contain a certain string

I am trying to obtain a list of columns in a DataFrame if any value in a column contains a string. For example in the below dataframe I would like a list of columns that have the % in the string. I am able to accomplish this using a for loop and the series.str.contains method but doens't seem optimal especially with a larger dataset. Is there a more efficient way to do this?

import pandas as pd

df = pd.DataFrame({'A': {0: '2019-06-01', 1: '2019-06-01', 2: '2019-06-01'},
                   'B': {0: '10', 1: '20', 2: '30'},
                   'C': {0: '10', 1: '20%', 2: '30%'},
                   'D': {0: '10%', 1: '20%', 2: '30'},
               })

DataFrame

            A   B    C    D
0  2019-06-01  10   10  10%
1  2019-06-01  20  20%  20%
2  2019-06-01  30  30%   30

Current Method

col_list = []
for col in df.columns:
    if (True in list(df[col].str.contains('%'))) is True:
        col_list.append(col)

Output

['C', 'D']
like image 450
MBasith Avatar asked Jun 21 '19 13:06

MBasith


2 Answers

stack with any

df.columns[df.stack().str.contains('%').any(level=1)]

Index(['C', 'D'], dtype='object')

comprehension

[c for c in df if df[c].str.contains('%').any()]

['C', 'D']

filter

[*filter(lambda c: df[c].str.contains('%').any(), df)]

['C', 'D']

Numpy's find

from numpy.core.defchararray import find

df.columns[(find(df.to_numpy().astype(str), '%') >= 0).any(0)]

Index(['C', 'D'], dtype='object')
like image 195
piRSquared Avatar answered Nov 16 '22 01:11

piRSquared


First use DataFrame.select_dtypes for filter only object columns, obviously string columns.

Then use DataFrame.applymap for elementwise check values with DataFrame.any for return True if at least one per column, so possible filter columns:

c = df.columns[df.select_dtypes(object).applymap(lambda x: '%' in str(x)).any()].tolist()
print (c)
['C', 'D']

Or use Series.str.contains per columns, na parameter should be omit if all strings columns:

f = lambda x: x.str.contains('%', na=False)
c = df.columns[df.select_dtypes(object).apply(f).any()].tolist()
print (c)
['C', 'D']
like image 44
jezrael Avatar answered Nov 16 '22 02:11

jezrael