How to split DateTime Data to create multiple feature in Python?
DATA MUNGING DATA CLEANING PYTHON MACHINE LEARNING RECIPES PANDAS CHEATSHEET     ALL TAGS

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

0

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'].dt.day
  • 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:

                 date
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

Relevant Projects

Machine Learning project for Retail Price Optimization
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

Data Science Project in Python on BigMart Sales Prediction
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

Topic modelling using Kmeans clustering to group customer reviews
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Predict Census Income using Deep Learning Models
In this project, we are going to work on Deep Learning using H2O to predict Census income.

Sequence Classification with LSTM RNN in Python with Keras
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.

Human Activity Recognition Using Multiclass Classification in Python
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.

Choosing the right Time Series Forecasting Methods
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.

Predict Macro Economic Trends using Kaggle Financial Dataset
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.