What is unstacking and squeeze in pandas dataframe?

What is unstacking and squeeze in pandas dataframe?

What is unstacking and squeeze in pandas dataframe?

This recipe explains what is unstacking and squeeze in pandas dataframe


Recipe Objective

Suppose we have a stacked data i.e. column is stacked row wise. Now we wish to unstack it. It can easily be done by unstack() function.

So this recipe is a short example on What is unstacking and squeeze in pandas dataframe. Let's get started.

Step 1 - Import the library

import pandas as pd import seaborn as sb

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays. Seaborn is just used in here to import dataset.

Step 2 - Setup the Data

df = sb.load_dataset('tips') stacked_df=df.stack() print(stacked_df)

Here we have imported tips dataset from seaborn library. Now, to produce a stacked dataframe, we are using stack function to modify the current.

Now our dataset is ready.

Step 3 - Unstacking dataframe.

unstacked_df=stacked_df.unstack() print(unstacked_df)

Here we unstacked our datafram using unstack() function.

Step 4 - Let's look at our dataset now

Once we run the above code snippet, we will see:

Scroll down to the ipython file to look at the results.

We can see data returning to original format. Similarity for multiindex format, we will have same results.

Relevant Projects

Predict Employee Computer Access Needs in Python
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

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.

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.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Predict Churn for a Telecom company using Logistic Regression
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

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.

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.