In this article, we will discuss a way to add a new column in DataFrame with the current datetime in Pandas.
Table Of Contents
Preparing DataSet
First we will create a DataFrame from list of tuples i.e.
import pandas as pd
# List of Tuples
employees= [('Mark', 'US', 'Tech', 5),
('Riti', 'India', 'Tech' , 7),
('Shanky', 'India', 'PMO' , 2),
('Shreya', 'India', 'Design' , 2),
('Aadi', 'US', 'Tech', 11),
('Sim', 'US', 'Tech', 4)]
# Create a DataFrame object from list of tuples
df = pd.DataFrame(employees,
columns=['Name', 'Location', 'Team', 'Experience'])
print(df)
Output:
0 Mark US Tech 5 1 Riti India Tech 7 2 Shanky India PMO 2 3 Shreya India Design 2 4 Aadi US Tech 11 5 Sim US Tech 4
Now, suppose we want to add a new column in this DataFrame ‘Last_Login_Time’, and this column should contain current DateTime. Let’s see how to do that.
Add Column with current datetime in Pandas
Pandas provides a new class Timestamp, and we can call its constructor with value ‘now’. It will give us a datetime64 object, containing the current date and time. To create a new column where all values should contain the current datetime, assign pd.Timestamp('now') to the [] operator of DataFrame i.e.
# Add new Column with current datetime in Pandas
df['Last_Login_Time'] = pd.Timestamp('now')
print(df)
Output
Frequently Asked:
Name Location Team Experience Last_Login_Time 0 Mark US Tech 5 2023-01-06 11:09:26.326084 1 Riti India Tech 7 2023-01-06 11:09:26.326084 2 Shanky India PMO 2 2023-01-06 11:09:26.326084 3 Shreya India Design 2 2023-01-06 11:09:26.326084 4 Aadi US Tech 11 2023-01-06 11:09:26.326084 5 Sim US Tech 4 2023-01-06 11:09:26.326084
It added a new column Last_Login_Time in the DataFrame, and each value of this new column is the current Date Time.
Add Column with current datetime with custom format in Pandas
To add a new column of current datetime in custom format, we can call the strftime() function on datetime object with custom format. For example,
df['Last_Logout_Time'] = pd.Timestamp('now').strftime("%Y/%m/%d %H:%M:%S:%f")
print(df)
df['Last_checkout_Time'] = pd.Timestamp('now').strftime("%y-%m-%d %H:%M:%S")
print(df)
Output:
Name Location Team Experience Last_Login_Time Last_Logout_Time
0 Mark US Tech 5 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
1 Riti India Tech 7 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
2 Shanky India PMO 2 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
3 Shreya India Design 2 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
4 Aadi US Tech 11 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
5 Sim US Tech 4 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950
Name Location Team Experience Last_Login_Time Last_Logout_Time Last_checkout_Time
0 Mark US Tech 5 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
1 Riti India Tech 7 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
2 Shanky India PMO 2 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
3 Shreya India Design 2 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
4 Aadi US Tech 11 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
5 Sim US Tech 4 2023-01-06 11:15:20.811131 2023/01/06 11:15:20:836950 23-01-06 11:15:20
It added new columns with current datetime, but in different format.
Summary
Today we learned about different ways to add a new column in dataFrame with current datetime in Pandas. Thanks.
