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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, weâ€™ll explore `sidetable`

, an extension of pandas library, to perform data analysis. Weâ€™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!