somal :
I want to get list of dataframe columns that contains all rows with 2 spaces.
Input:
import pandas as pd
import numpy as np
pd.options.display.max_columns = None
pd.options.display.max_rows = None
pd.options.display.expand_frame_repr = False
df = pd.DataFrame({'id': [101, 102, 103],
'full_name': ['John Brown', 'Bob Smith', 'Michael Smith'],
'comment_1': ['one two', 'qw er ty', 'one space'],
'comment_2': ['ab xfd xsxws', 'dsd sdd dwde', 'wdwd ofjpoej oihoe'],
'comment_3': ['ckdf cenfw cd', 'cewfwf wefep lwcpem', np.nan],
'birth_year': [1960, 1970, 1970]})
print(df)
Output:
id full_name comment_1 comment_2 comment_3 birth_year
0 101 John Brown one two ab xfd xsxws ckdf cenfw cd 1960
1 102 Bob Smith qw er ty dsd sdd dwde cewfwf wefep lwcpem 1970
2 103 Michael Smith one space wdwd ofjpoej oihoe NaN 1970
Expected Output:
['comment_2', 'comment_3']
G. Anderson :
You can use series.str.count() to count the appearances of a substring or pattern in a string, use .all() to check whether all items meet the criteria, and iterate over df.columns using only string columns with select_dtypes('object')
[i for i in df.select_dtypes('object').columns if (df[i].dropna().str.count(' ')==2).all()]
['comment_2', 'comment_3']
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