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Combining columns containing date and time in Pandas

Pandas
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Time Series Cookbook
schedule Jul 1, 2022
Last updated
local_offer 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 B
0 2020-12-22 15:30:00
1 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 C
0 2020-12-22 15:30:00 2020-12-22 15:30:00
1 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 15:30:00
1 2020-12-23 16:30:00
dtype: 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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Published by Isshin Inada
Edited by 0 others
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