How to make a graph with animation in plotly?
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

How to make a graph with animation in plotly?

How to make a graph with animation in plotly?

This recipe helps you make a graph with animation in plotly

0

Recipe Objective

Make a graph with animation included in it.

Animation while plotting the graph it need to be interactive so for that animation also helps in interactive visualization. Function can be used by "animation_frame" and "animation_group" arguments. Make sure that we should always fix the x_range and y_range to ensure that your data remains visible throughout the animation.

Step 1 - Import the necessary libraries

import plotly.express as px

Step 2 - load the Sample data

Sample_data = px.data.gapminder() Sample_data.head()

Step 3 - Plot the graph

fig = px.scatter(Sample_data, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country", size="pop", color="continent", hover_name="country", facet_col="continent", log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90], ) fig.show()

Here in the above figure various functions been used:

X - determine the column to be plotted on X-axis.

Y - determine the column to be plotted on Y-axis.

size - will plot the data points on the graph according to the column that we have mentioned.

color - will plot the points in colored on graph according to the column that we have mentioned.

hover_name - should be a column name, here we have given "country" column which will gives the details about the data.

facet_col - values from this are used to assign marks to facetted subplots in the horizontal direction.

animation_frame - values from this are used to assign marks to animation frame.

animation_group - values from this are used to provide object-constancy across animation frames: rows with matching animation_groups will be treated as if they describe the same object in each frame.

range_x - these are list of two numbers used for overriding auto-scaling on the x-axis in cartesian coordinates.

range_y - these are list of two numbers used for overriding auto-scaling on the y-axis in cartesian coordinates.

Relevant Projects

Resume parsing with Machine learning - NLP with Python OCR and Spacy
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

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.

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.

Loan Eligibility Prediction in Python using H2O.ai
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.

Build a Similar Images Finder with Python, Keras, and Tensorflow
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.

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.

Build a Music Recommendation Algorithm using KKBox's Dataset
Music Recommendation Project using Machine Learning - Use the KKBox dataset to predict the chances of a user listening to a song again after their very first noticeable listening event.

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.

PySpark Tutorial - Learn to use Apache Spark with Python
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

Zillow’s Home Value Prediction (Zestimate)
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.