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# Combining columns containing date and time in Pandas

schedule Aug 12, 2023
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PythonPandas
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Consider the following DataFrame:

``` df = pd.DataFrame({"A":["2020-12-22","2020-12-23"], "B":["15:30:00","16:30:00"]})df A B0 2020-12-22 15:30:001 2020-12-23 16:30:00 ```

Here, column `A` represents the date unit while `B` represents the time unit. They are both of type `string`.

# Solution

To add a new column `C` of type `datetime64` that combines `A` and `B`:

``` df["C"] = pd.to_datetime(df["A"] + " " + df["B"])df A B C0 2020-12-22 15:30:00 2020-12-22 15:30:001 2020-12-23 16:30:00 2020-12-23 16:30:00 ```

# Explanation

We first make a Series of datetime strings using concatenation:

``` df["A"] + " " + df["B"] 0 2020-12-22 15:30:001 2020-12-23 16:30:00dtype: object ```

The space `" "` is essential - the conversion to `datetime64` is not possible without it.

We then use `to_datetime(~)` method to convert the datetime strings into type `datetime64`.

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