How can I filter a dataframe of dates with other date in Python?

Question

I have this dataframe in python done in pandas:

        0
0   2018-06-29
1   2018-10-29
2   2019-02-28
3   2019-06-29
4   2019-10-29
5   2020-02-29
6   2020-06-29
7   2020-10-29
8   2021-02-28

Then I have a date that is the next one:

[datetime.date(2020, 2, 29)]

I want to filter the data frame to get just the dates that are <= that the date I have. I tried this with loc[] but I get the next output:

Seleccion = df.loc[df[0] < date]
Arrays were different lengths: 9 vs 1

I don't know if there is a way to do that, but if it is, any help would be perfect. Thank you for taking your time.

You don't need the .iloc just do selection = df[df['0'] < date] — T Burgis
– T Burgis, Commented Oct 31, 2018 at 11:16

VaM · Accepted Answer · 2018-10-31 11:57:19Z

1

What is the value of "date" on your example? If it is

date = [datetime.date(2020, 2, 29)]

then it is normal the error is happening because you are comparing a series to an array.

What you want to do is

date = datetime.date(2020, 2, 29)
df[df[0] < date]

because now you are comparing a Series with a constant, and pandas is able to transform it into a comparison row-wise over the Series.

Before you were comparing a Series with an array (even if it has a single element), and for that to work, the array had to have the same length as the Series.

edited Oct 31, 2018 at 11:57

answered Oct 31, 2018 at 11:36

VaM

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3 Comments

T Burgis Over a year ago

You have a typo in df.[df[0] < date], get rid of the .

Amartin Over a year ago

That works but if there a way to convert the array in a datetime.date object? @TBurgis

VaM Over a year ago

Which variable are you calling "the array"? I assumed the datatype of df[0] was a datetime.date object. If you need to convert it use the pd.to_datetime and then look into link.

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