Pandas: Create a Series of Timestamps from a DataFrame of integer or string columns

Last update on May 02 2025 12:55:59 (UTC/GMT +8 hours)

13. Series of Timestamps from DataFrame

Write a Pandas program to create a series of Timestamps from a DataFrame of integer or string columns. Also create a series of Timestamps using specified columns.

Sample Solution:

Python Code :

import pandas as pd
df = pd.DataFrame({'year': [2018, 2019, 2020],
                   'month': [2, 3, 4],
                   'day': [4, 5, 6],
                   'hour': [2, 3, 4]})
print("Original dataframe:")
print(df)
result = pd.to_datetime(df)
print("\nSeries of Timestamps from the said dataframe:")
print(result)
print("\nSeries of Timestamps using specified columns:")
print(pd.to_datetime(df[['year', 'month', 'day']]))

Sample Output:

Original dataframe:
   year  month  day  hour
0  2018      2    4     2
1  2019      3    5     3
2  2020      4    6     4

Series of Timestamps from the said dataframe:
0   2018-02-04 02:00:00
1   2019-03-05 03:00:00
2   2020-04-06 04:00:00
dtype: datetime64[ns]

Series of Timestamps using specified columns:
0   2018-02-04
1   2019-03-05
2   2020-04-06
dtype: datetime64[ns]

For more Practice: Solve these Related Problems:

Write a Pandas program to create a series of Timestamps from a DataFrame containing separate year, month, and day columns.
Write a Pandas program to convert multiple date-related string columns into a unified Timestamp series and sort the result.
Write a Pandas program to extract and combine date components from a DataFrame into a Timestamp series and then validate the data type.
Write a Pandas program to create a Timestamp series using specified columns and then set it as the DataFrame index.

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Next: Write a Pandas program to check if a day is a business day (weekday) or not.

Python Code Editor:

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