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Interactive Data Visualization with Python - Second Edition

You're reading from  Interactive Data Visualization with Python - Second Edition

Product type Book
Published in Apr 2020
Publisher
ISBN-13 9781800200944
Pages 362 pages
Edition 2nd Edition
Languages
Authors (4):
Abha Belorkar Abha Belorkar
Profile icon Abha Belorkar
Sharath Chandra Guntuku Sharath Chandra Guntuku
Profile icon Sharath Chandra Guntuku
Shubhangi Hora Shubhangi Hora
Profile icon Shubhangi Hora
Anshu Kumar Anshu Kumar
Profile icon Anshu Kumar
View More author details
Toc

Table of Contents (9) Chapters close

Preface 1. Introduction to Visualization with Python – Basic and Customized Plotting 2. Static Visualization – Global Patterns and Summary Statistics 3. From Static to Interactive Visualization 4. Interactive Visualization of Data across Strata 5. Interactive Visualization of Data across Time 6. Interactive Visualization of Geographical Data 7. Avoiding Common Pitfalls to Create Interactive Visualizations Appendix

2. Static Visualization – Global Patterns and Summary Statistics

Activity 2: Design Static Visualization to Present Global Patterns and Summary Statistics

Solution

  1. Load the necessary python modules and download the Olympic History dataset hosted in the book's GitHub repository, and format it as a pandas DataFrame:
    # load necessary modules
    import pandas as pd
    import seaborn as sns
    from numpy import median, mean
    # download file 'athlete_events.csv' from course GitHub repository: https://github.com/TrainingByPackt/Interactive-Data-Visualization-with-Python/datasets
    # read the dataset as a pandas DataFrame
    olympics_df = pd.read_csv('../Interactive-Data-Visualization-with-Python-master/datasets/athlete_events.csv')
    # preview DataFrame
    olympics_df.head()

    The output is as follows:

    Figure 2.22: Olympic History dataset
  2. Filter the DataFrame to contain only the medal winners of the year 2016 for the sports mentioned in the activity description:
    # filter...
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