Pandas: Create a Series of Timestamps from a DataFrame of integer or string columns
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]
Python Code Editor:
Have another way to solve this solution? Contribute your code (and comments) through Disqus.
Previous: Write a Pandas program to convert year and day of year into a single datetime column of a dataframe.
Next: Write a Pandas program to check if a day is a business day (weekday) or not.
What is the difficulty level of this exercise?
Test your Programming skills with w3resource's quiz.
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics