str.contains function AND does not contain

user_18152569 0
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I'm iterating over all values in columns that contain 'Applicant Age' and adding them into a new column.

for i in range(17):
    rule_col = f'rule{i}_evaluationstring'
    matches = df_merged[rule_col].astype(str).str.contains('Applicant Age', na=False)
    df_merged.loc[matches, 'applicant_age'] = df_merged.loc[matches, rule_col]

This works properly, but there are some entries that have an 'Applicant Age = 200' that I would like to omit.

How do I add an additional function that omits all values that contain 200 while keeping the functionality of the above?

pandas dataframe numpy python
2 Answers

You can use the bitwise operators & (and) and ~ (not) in combination. The syntax looks like df.loc[(condition_A) & (~condition_B)]

An example relevant for your question would be:

df = df_merged

selected = df.loc[
    (df[rule_col].astype(str).str.contains('Applicant Age', na=False)) &
    (~df[rule_col].astype(str).str.contains('200', na=False))
]
user_31900760

Try this:

matches = (df_merged[rule_col].astype(str).str.contains('Applicant Age', na=False)) & (~df_merged[rule_col].astype(str).str.contains('Applicant Age = 200', na=False))
user_53537530
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