CODEWITHSUNDEEP
pythonpandasdataframefilter
oakca
oakca

Reputation: 1568

Filtering pandas df with conditions

I have a pandas df:

df
                          DEtoDK         DKtoDE         
                            self other     self    other
2021-01-01 00:00:00+00:00    0.0   NaN  2230.08      NaN
2021-01-01 01:00:00+00:00    0.0   0.0  1887.72  2230.08
2021-01-01 02:00:00+00:00    0.0   0.0  1821.33  1887.72
2021-01-01 03:00:00+00:00    0.0   0.0  1743.20  1821.33
2021-01-01 04:00:00+00:00    0.0   0.0  1720.78  1743.20
...                          ...   ...      ...      ...
2021-05-31 19:00:00+00:00    0.0   0.0   782.88   892.16
2021-05-31 20:00:00+00:00    0.0   0.0   872.96   782.88
2021-05-31 21:00:00+00:00    0.0   0.0  1165.36   872.96
2021-05-31 22:00:00+00:00    0.0   0.0  1418.32  1165.36
2021-05-31 23:00:00+00:00    0.0   0.0  1393.28  1418.32
[3624 rows x 4 columns]

I would like to filter this df, with some conditions like, if the (DEtoDK, self) or (DKtoDE, self) values are 0. For that I am using the following:

df.loc[(df[('DEtoDK', 'self')].values == 0) | (df[('DKtoDE', 'self')].values == 0)]

And this works, however when the df does not have any 0 values then I was expecting to generate an empty dataframe, however I am getting a KeyError.

df.loc[(df[('DEtoDK', 'self')].values == 'test') | (df[('DKtoDE', 'self')].values == 'test')]
KeyError: False

so the conditions are generating False, instead of an empty array, therefore pandas cannot locate. How can I fix this behaviour?

Upvotes: 2

Views: 88

Answers (1)

U13-Forward
U13-Forward

Reputation: 71560

No need for values:

df.loc[(df[('DEtoDK', 'self')] == 0) | (df[('DKtoDE', 'self')] == 0)]

Upvotes: 3

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