Shorter way of boolean indexing in pandas (Series and DataFrame)?

Question

I want to know if there is a shorter way for boolean indexing in pandas? Nowadays I make like that:

s = pd.Series(...)
s[s>0]

But it becomes cumbersome when the variable has a long name or if I do not have the Series/DataFrame stored in a variable.

results_of_the_query[results_of_the_query['code'] == 200]

or

stocks.get('AAPL').intraday_quotes.loc[stocks.get('AAPL').intraday_quotes['time']='9:00']

You have to access it somehow. Maybe look into making a view? — Akaisteph7, Jul 22 '19 at 00:04
[Check this out](https://stackoverflow.com/questions/53779986/dynamic-expression-evaluation-in-pandas-using-pd-eval): `results_of_the_query.query('code == 200')` — cs95, Jul 22 '19 at 00:07

score 2 · Accepted Answer · answered Jul 22 '19 at 00:31

2

Let us do loc

For Series

s.loc[lambda x : x >0]

For DataFrame

df.loc[lambda x : x['code']>0]

answered Jul 22 '19 at 00:31

BENY

1 Answers1