Check if value is in Pandas dataframe column

Question

I've having an issue checking is a value is in the following dataframe:

index	open	high	PositionEMA25M50M
2021-03-30 05:35:00	0.000059	0.000059	-1.0
2021-03-30 05:40:00	0.000059	0.000059	0.0
2021-03-30 05:45:00	0.000059	0.000059	0.0

i am trying to simply return true if the PositionEMA25M50M contains -1.0

i have tried:

if -1.0 in indicator_5min_df.PositionEMA25M50M:
    print('true')
else:
    print('false')

however this returns false every time... i assume this is something to do with PositionEMA25M50M being of type float64 however i've also tried

if np.float64(-1.0) in indicator_5min_df.PositionEMA25M50M:
    print('true')
else:
    print('false')

which has given me the same result...

any ideas how i can fix this?

@jezrael Wrong dupe. OP wants to return `True` as well. Please attach a proper dupe or open the question. — Mayank Porwal, Mar 30 '21 at 06:21
First dupe explain `in` why not working, second using `any` or `all` for test. — jezrael, Mar 30 '21 at 06:24
No. That is wrong. This way you can close all questions that are asked. — Mayank Porwal, Mar 30 '21 at 06:26
hmmm, so if you think only second dupe matching, first be free remove. — jezrael, Mar 30 '21 at 06:26
Ok, explanation `No dupe is completely matching` is not very clear. — jezrael, Mar 30 '21 at 06:37
I think correct dupe is [this](https://stackoverflow.com/questions/21319929/how-to-determine-whether-a-pandas-column-contains-a-particular-value) — jezrael, Mar 30 '21 at 06:38

Mayank Porwal · Accepted Answer · 2021-03-30T06:35:14.473

1

You don't need a if loop. You can directly use Series.eq with any to check if any row has -1 for this column:

In [990]: df['PositionEMA25M50M'].eq(-1).any()
Out[990]: True

edited Mar 30 '21 at 06:35

answered Mar 30 '21 at 06:18

Mayank Porwal

dupe https://stackoverflow.com/questions/21319929/how-to-determine-whether-a-pandas-column-contains-a-particular-value – jezrael Mar 30 '21 at 06:38

1 Answers1