Filter dataframe by datetime.date column

[glidecode]

I usually filter for data like this: df[df.somecolumn > 10]

However, I haven't been able to do this for a column I have in type "datetime.date"

If I do: df[df["date"] == "2020-11-30"]) I get nothing returned and no error message.

I have been googling for hours trying to fix this, so any input is welcome.

EDIT - I found a solution

I can do it like this: df[df["date"] == datetime.date(2020,11,30)])

I'm not sure why it can be done without this tweak for datetime64, but that format seems to be easier to use in this regard

[snippsat]

You most make sure that date column is convert to pandas date format datetime64[ns].
Example

import pandas as pd

data = {
    "Salary": [1000, 2222, 3321, 4414, 5151],
    "Name": ["Pete", "Steve", "Brian", "Ryan", "Jim"],
    "Share": [29.88, 19.05, 8.17, 7.3, 6.15],
    "Date": [
        "11/24/2020",
        "12/21/2019",
        "10/14/2018",
        "12/13/2017",
        "01/08/2017",
    ],
}

df = pd.DataFrame(data) 

See that Date is object.

>>> df
   Salary   Name  Share        Date
0    1000   Pete  29.88  11/24/2020
1    2222  Steve  19.05  12/21/2019
2    3321  Brian   8.17  10/14/2018
3    4414   Ryan   7.30  12/13/2017
4    5151    Jim   6.15  01/08/2017

>>> df.dtypes
Salary      int64
Name       object
Share     float64
Date       object
dtype: objec

>>> df[df["Date"] == "2018-10-14"]
Empty DataFrame
Columns: [Salary, Name, Share, Date]
Index: []

Fix.

import pandas as pd

data = {
    "Salary": [1000, 2222, 3321, 4414, 5151],
    "Name": ["Pete", "Steve", "Brian", "Ryan", "Jim"],
    "Share": [29.88, 19.05, 8.17, 7.3, 6.15],
    "Date": [
        "11/24/2020",
        "12/21/2019",
        "10/14/2018",
        "12/13/2017",
        "01/08/2017",
    ],
}

df = pd.DataFrame(data)
df['Date'] = pd.to_datetime(df['Date'])
print(df[df["Date"] == "2018-10-14"])

Output:
   Salary   Name  Share       Date
2    3321  Brian   8.17 2018-10-14

[glidecode]

Thanks for the input!

I have a further problem

I have a separate dataframe where the "date" column is in the format: <class 'pandas._libs.tslibs.timestamps.Timestamp'>

I want to filter the dataframe and return all rows where "date" is either a particular date or is in some interval.

If I do something like this I get the error: The truth value of a Series is ambiguous.

 (df["2020-01-01 00:00:00" < df["date"] < "2020-02-02 00:00:00"]) 

I have tried for hours but every google result has some variation I can't fix this by.