Pandas: Indexing by date and time

Last update on May 01 2025 12:56:02 (UTC/GMT +8 hours)

6. DataFrame Indexed by Date and Time

Write a Pandas program to create a dataframe indexing by date and time.

Test Data:

0        s001     V  Alberto Franco     15/05/2002      35  street1   t1
1        s002     V    Gino Mcneill     17/05/2002      32  street2   t2
2        s003    VI     Ryan Parkes     16/02/1999      33  street3   t3
3        s001    VI    Eesha Hinton     25/09/1998      30  street1   t4
4        s002     V    Gino Mcneill     11/05/2002      31  street2   t5
5        s004    VI    David Parkes     15/09/1997      32  street4   t6

Sample Solution:

Python Code :

import pandas as pd
print("Create a dataframe, indexing by date and time:")

dt_range = pd.date_range(start ='2020-05-12 07:10:10', freq ='S', periods = 10) 
df_dt = pd.DataFrame({"Sale_amt":[100, 110, 117, 150, 112, 99, 129, 135, 140, 150]},
                            index = dt_range)
print(df_dt)

Sample Output:

Create a dataframe, indexing by date and time:
                     Sale_amt
2020-05-12 07:10:10       100
2020-05-12 07:10:11       110
2020-05-12 07:10:12       117
2020-05-12 07:10:13       150
2020-05-12 07:10:14       112
2020-05-12 07:10:15        99
2020-05-12 07:10:16       129
2020-05-12 07:10:17       135
2020-05-12 07:10:18       140
2020-05-12 07:10:19       150

For more Practice: Solve these Related Problems:

Write a Pandas program to create a DataFrame with a datetime index using a date range and then display the DataFrame.
Write a Pandas program to set a DataFrame index to a series of date and time values and then filter the DataFrame based on a date range.
Write a Pandas program to generate a DataFrame indexed by dates and times, and then resample the data by day.
Write a Pandas program to create a DataFrame with a datetime index and then convert the index to a different time zone.

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Python Code Editor:

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