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Data Analysis & Visualization with Python

This guide was created for those interested in learning about creating visualizations in Python using the plotly package.


Looking to learn how to make charts and graphs with Python programming?

Use this guide to learn about basic principles, structures, and operations in Python.

You will be introduced to the following outcomes:

  • Install and import the pandas and plotly libraries (Installing and Importing the Libraries)
  • Import .csv files using Python and panda (Importing and Previewing Data)
  • Produce descriptive statistics for textual and numeric data (Cleaning Your Data)
  • Replace missing values with column mean (Cleaning Your Data)
  • Change column names (Cleaning Your Data)
  • Change column data type (Cleaning Your Data)
  • Subset dataset based on a condition (Cleaning Your Data)
  • Split columns based on a delimiter (Cleaning Your Data)
  • Determine correlation of numeric data (Analyzing Your Data)
  • Produce descriptive statistics for textual and numeric data (Analyzing Your Data)
  • Create customized histograms, bar charts, pie charts, and box-and-whisker for univariate analysis (Univariate Visualizations)
  • create customized line graphs for time series analysis (Time-series Visualizations)
  • create customized stacked and grouped bar charts, scatter plots, and box plots for bivariate analysis (Bi-/Multi-Variate Visualizations)
  • Save data visualizations for use in presentations and other written communication (Saving and Exporting Visualizations)
  • locate Python related resources in the University Libraries’ catalog (Related Library Resources)

What is Python?


Python is a programming language that can be used for a variety of data-intensive tasks from descriptive analytics to machine learning. With the help of community-created library packages, you can use Python to tackle your next academic, professional, or personal data project! For more information about Python, visit the following site:  Welcome to Python

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.