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You will learn to:
Perform basic exploratory data analysis.
Analyze data with sidetable.
Visualize data using Bokeh.
Understand the patterns in the data.
Skills
Data Visualization
Data Science
Data Manipulation
Prerequisites
Familiarity with Python
Understanding of data preprocessing
Basic understanding of data visualization
Technologies
NumPy
Bokeh
Python
Pandas
Project Description
Data is everywhere, and to make proper sense of it, data analysis plays an important role. Data analysis discovers hidden patterns in the pile of data that eventually lead to more purposeful use of data in decision-making. However, visuals communicate the analysis results more quickly than numbers and tables. Therefore, data analysis and data visualizations go hand in hand.
In this project, we’ll explore sidetable, an extension of pandas library, to perform data analysis. We’ll also learn how to display the gist of these analyses via visualizations created with the Bokeh library.
Project Tasks
1
Prerequisites
Task 0: Get Started
Task 1: Import Libraries
Task 2: Load the Dataset
2
Data Analysis
Task 3: Explore the Dataset
Task 4: Treat Missing Values
Task 5: Inspect Class Distribution
Task 6: Display Class Imbalance as Histogram
Task 7: Explore the Categorical Variables
Task 8: Visualize Data Distribution in Categorical Variables
Task 9: Explore Trends via Continuous Variables
Congratulations!
Relevant Courses
Use the following content to review prerequisites or explore specific concepts in detail.