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# Adding new column containing the difference between two date columns in Pandas DataFrame

Pandas
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Time Series Cookbook
schedule Jul 1, 2022
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Consider the following DataFrame:

``` dates1 = pd.date_range(start="2020/12/15", periods=3)dates2 = pd.date_range(start="2020/12/20", periods=3, freq="2D")df = pd.DataFrame({"A":dates1, "B":dates2})df A B0 2020-12-15 2020-12-201 2020-12-16 2020-12-222 2020-12-17 2020-12-24 ```

Pandas allows for date arithmetics using the standard binary operators (e.g. `+`, `-`):

``` df["C"] = df["B"] - df["A"]df A B C0 2020-12-15 2020-12-20 5 days1 2020-12-16 2020-12-22 6 days2 2020-12-17 2020-12-24 7 days ```

Here, column `C` is of type `timedelta64[ns]`, which explains why the term `"days"` is appended. To remove the `"days"`, use `dt.days` to extract the day unit as an `int64`:

``` df["C"] = (df["B"] - df["A"]).dt.daysdf A B C0 2020-12-15 2020-12-20 51 2020-12-16 2020-12-22 62 2020-12-17 2020-12-24 7 ```
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