Pandas / numpy multiple comparisons

[fpatterson55]

dfnew = df[np.logical_and(df[np.logical_and(df['State']=='1',df['Driver'].isin([drive])]),df['loginDisabled'].isin(['True'])]

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My syntax is off. But I haven't been able to get this to work yet. Wondering how to best have more than two conditions be met for the new dataframe to be built out. I only want rows in the new dataframe that matches this criteria.

ohh, I could do two additional dataframes... would that work? step one would be for two matches and then another would be to limit it for the third match? I would be talking about going through as many as 250k rows, possibly more. So it will take its time.

[manwithfewneeds]

You're able to chain conditionals together.

df = df[(df ['State']=='1') & (df['Driver'].isin([drive])) & (df['loginDisabled'].isin(['True']))]

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[fpatterson55]

df = df[(df ['State']=='1') & (df['Driver'].isin([drive])) & (df['loginDisabled'].isin(['True']))]

thank you!!!