Combining columns of years, months and days in Pandas

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schedule Jul 1, 2022

Last updated

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Solution

To combine the Year, Month and Day columns to form another column:


        
        
            
                
                
                    df["Date"] = pd.to_datetime(df["Year"] + "/" + df["Month"] + "/" + df["Day"])
df
                
            
               Year   Month  Day  Date
0  2020   10     25   2020-10-25
1  2020   11     26   2020-11-26

Here, column Date is of type datetime.

Explanation

We first combine Year, Month and Day columns via simple string concatenation:


        
        
            
                
                
                    df["Year"] + "/" + df["Month"] + "/" + df["Day"]
                
            
            0    2020/10/25
1    2020/11/26
dtype: object

Here, the combined column (Series) is of type string. We can convert its data type to datetime using pd.to_datetime(~):


        
        
            
                
                
                    pd.to_datetime(df["Year"] + "/" + df["Month"] + "/" + df["Day"])
                
            
            0   2020-10-25
1   2020-11-26
dtype: datetime64[ns]