marwan1023 / data-visualization

Data-Visualization

Introduction The aim of these labs is to introduce you to data visualization with Python as concrete and as consistent as possible. Speaking of consistency, because there is no best data visualization library avaiblable for Python - up to creating these labs - we have to introduce different libraries and show their benefits when we are discussing new visualization concepts. Doing so, we hope to make students well-rounded with visualization libraries and concepts so that they are able to judge and decide on the best visualitzation technique and tool for a given problem and audience.

Please make sure that you have completed the prerequisites for this course, namely Python for Data Science and Data Analysis with Python, which are part of this specialization.

Note: The majority of the plots and visualizations will be generated using data stored in pandas dataframes. Therefore, in this lab, we provide a brief crash course on pandas. However, if you are interested in learning more about the pandas library, detailed description and explanation of how to use it and how to clean, munge, and process data stored in a pandas dataframe are provided in our course Data Analysis with Python, which is also part of this specialization.

Table of Contents

Exploring Datasets with pandas

1 The Dataset: Immigration to Canada from 1980 to 2013

2 pandas Basics

3 pandas Intermediate: Indexing and Selection

Visualizing Data using Matplotlib

1 Matplotlib: Standard Python Visualization Library

Line Plots