I am trying to search through specific columns in my DataFrame. If any of these columns contains the keyword "Matched" I would then like to write to the column "Result" with a "Yes"
Current DF
Result Google Bing Search
Matched Matched Matched
Matched
Matched
Expected Result
Result Google Bing Search
Yes Matched Matched Matched
No
Yes Matched
Yes Matched
Use numpy.where with test values by DataFrame.eq with DataFrame.any for test at least one value per row:
cols = ['Google', 'Bing', 'Search']
df['Result'] = np.where(df[cols].eq('Matched').any(axis=1), 'Yes','No')
print (df)
Result Google Bing Search
0 Yes Matched Matched Matched
1 No NaN NaN NaN
2 Yes Matched NaN NaN
3 Yes NaN Matched NaN
Try using a list comprehension like this:
df['Result'] = ['Yes' if len(i) >= 1 else 'No' for i in df.values.tolist()]
