How to split DateTime Data to create multiple feature in Python?

How to split DateTime Data to create multiple feature in Python?

How to split DateTime Data to create multiple feature in Python?

This recipe helps you split DateTime Data to create multiple feature in Python


Recipe Objective

Many a times in a dataset we find Date Time Stamps which is the combination of Date and Time written in a perticular format. For analysis we have to split the Data Time Stamp such that we can get different information seperately like Year, Month, Day, Hour, Minute and Seconds. This can be easily done by using pandas.

So this is the recipe on how we can split DateTime Data to create multiple feature in Python.

Step 1 - Import the library

import pandas as pd

We have imported only pandas which is requied for this split.

Step 2 - Setting up the Data

We have created an empty dataframe then we have created a column 'date'. By using date_range function we have created a dataset of date time stamp by passing the parameters of starting date, periods i.e number of stamps and frequency as weekly. df = pd.DataFrame() df['date'] = pd.date_range('1/6/2020 01:00:00', periods=6, freq='W') print(df)

Step 3 - Creating features of Date Time Stamps

We have to split the date time stamp into few features like Year, Month, Day, Hour, Minute and Seconds. For each of the feature split there are pre defined functions.

  • Creating the year column form date time stamp.
  • df['year'] = df['date'].dt.year
  • Creating the month column form date time stamp.
  • df['month'] = df['date'].dt.month
  • Creating the day column form date time stamp.
  • df['day'] = df['date']
  • Creating the hour column form date time stamp.
  • df['hour'] = df['date'].dt.hour
  • Creating the hour column form date time stamp.
  • df['hour'] = df['date'].dt.hour
Now we are printing the final dataset and the output comes as:

0 2020-01-12 01:00:00
1 2020-01-19 01:00:00
2 2020-01-26 01:00:00
3 2020-02-02 01:00:00
4 2020-02-09 01:00:00
5 2020-02-16 01:00:00

                 date  year  month  day  hour  minute
0 2020-01-12 01:00:00  2020      1   12     1       0
1 2020-01-19 01:00:00  2020      1   19     1       0
2 2020-01-26 01:00:00  2020      1   26     1       0
3 2020-02-02 01:00:00  2020      2    2     1       0
4 2020-02-09 01:00:00  2020      2    9     1       0
5 2020-02-16 01:00:00  2020      2   16     1       0

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