Three-Project Series

Data Visualization with Matplotlib and Seaborn you own this product

prerequisites
basic to intermediate Python 3 programming skills • familiarity with Anaconda Python • familiarity with Jupyter Notebook • basic NumPy • basic pandas • familiarity with Matplotlib plotting library
skills learned
use pandas functions to read data from CSV files into a data frame object • use import statement to load required libraries and modules into Jupyter Notebook • use API/functions from Matplotlib and seaborn to create, customize, save 2D and 3D plots
Nimrita Koul
3 weeks · 6-8 hours per week average · BEGINNER
filed under
includes 3 liveProjects
liveProject $35.99 $59.99 self-paced learning

In this series of liveProjects, you’re a data analyst hired to visualize data for two different companies. In the first two liveProjects, you’ll help ABC Bikes Inc. make informed decisions about its dynamic bike rental service by providing important insights about bike rental trends. Using Matplotlib, you’ll create 2D and 3D plots to determine the busiest hours for rental bikes and how weather, time of day, and month of year impact rentals.

In the third liveProject, you’ll gather insights for the Global Consensus Bureau company to analyze data from a survey conducted by the U.S. Census Bureau to determine how factors like education, hours worked per week, gender, and age relate to citizens’ incomes. Using Python’s seaborn library, which provides functions for customizing visual elements, you’ll create visually appealing charts that identify the statistical relationships you’re interested in. When you’ve completed this series, you’ll have the experience and knowledge to use Python’s Matplotlib and seaborn libraries to create attractive visualizations that provide useful insights.

These projects are designed for learning purposes and are not complete, production-ready applications or solutions.
Get Your Certificate of Completion—Free!
Finish the work in this liveProject to earn a Certificate of Completion. Once you’re done with your build, take a short online test, then contact the liveProject mentor who will review your submissions. Finally, set up a 15-minute video call with the mentor to verify your work.

I think that for people that need to do quick visualization and analytics of data, this series will be a useful training tool.

Brandon Hunt, Solution Architect, Intrado

here's what's included

Project 1 2D Plotting with Matplotlib

ABC Bikes Inc. is considering launching a bike rental service in your area. As the company’s data analyst, your task is to provide decision-driving insights on bike rental trends. You’ll extract the relevant data from a publicly available dataset into a pandas data frame. Then, using Python plotting library Matplotlib, you’ll create line plots to visualize changes for bike rentals on a single day as well as over a specific time period, create a grouped bar plot to visualize a comparison of renting data for two years, create subplots with different chart types, and create a violin plot to visualize renting patterns over four seasons. When you’re done, you’ll know how to use Matplotlib to create accurate and informative 2D visualizations.

$29.99 $19.49
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Project 2 3D Plotting with Matplotlib

ABC Bikes Inc. is considering expanding its bike rental service to a new county. Your job, as the company’s data analyst, is to determine factors that impact the demand for rental bikes in that area. You’ll extract the relevant data from a publicly available dataset into a pandas data frame. Then, using Matplotlib’s mplot3d toolkit, you’ll plot 3D graphs to simultaneously visualize more than two data features, enabling you to determine useful patterns including how temperature, time of day, and month of year impact bike rentals. When you’re finished, you’ll know how to use Matplotlib to create, customize, and rotate your 3D plots to gather useful and interesting insights.

$29.99 $19.49
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Project 3 Plotting with Seaborn

You’re a data analyst at Global Consensus Bureau, and your manager has asked you to determine how factors like education, hours worked per week, gender, and age relate to citizens’ incomes. Using pandas, you’ll pre-process data from a survey conducted by the U.S. Census Bureau. Then, you’ll create different charts to identify statistical relationships in data, using Python’s seaborn library, which provides custom functions for visual elements. When you’re done, you’ll know how to use seaborn to create visually appealing charts that reveal accurate and useful insights.

$29.99 $19.49
add to cart

project author

Nimrita Koul

Nimrita Koul is an assistant professor of Computer Science and Machine Learning from Bangalore, India. She holds a Phd in Computer Science with 16 years of experience in teaching Computer Science courses to University undergraduates. Nimrita is a principal investigator for three funded research projects in machine learning. She has designed and demonstrated about 20 data science and machine learning projects to more than 650 students. Nimrita has spoken at multiple international conferences and events.

Prerequisites

These liveProjects are for early career data analysts. To begin these liveProjects you’ll need to be familiar with the following:

TOOLS
  • Basic to intermediate Python 3 programming skills
  • Familiarity with Anaconda Python
  • Familiarity with Jupyter Notebook
TECHNIQUES
  • Install Anaconda Distribution of Python (preferred)
  • Install Python
  • Install/upgrade Jupyter Notebook (if not using Anaconda Distribution)
  • Install required Python Libraries: NumPy, pandas, Matplotlib, seaborn using pip or conda (if not using Anaconda Distribution)
  • Add, delete, move, and select cells (code and markdown) in Jupyter Notebook
  • Execute a code cell in Jupyter Notebook

you will learn

In this liveProject series, you’ll create useful visualizations of interesting insights from data using Matplotlib and seaborn Python libraries.

  • Read data from a CSV file into a pandas dataframe and extract the appropriate subset from it
  • Determine the suitable plot type to draw based on the type of insight required
  • Import required libraries and initialize the required environment for plotting
  • Draw interesting plots with data
  • Draw Subplots with shared axes
  • Customize your plots with color schemes, annotations, tick marks, etc.
  • Export/save your plots as image files and PDF files on your hard drive
  • Set the resolution of your plots before saving

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
Get Your Certificate of Completion—Free!
Finish the work in this liveProject to earn a Certificate of Completion. Once you’re done with your build, take a short online test, then contact the liveProject mentor who will review your submissions. Finally, set up a 15-minute video call with the mentor to verify your work.

The instructor put finished diagrams to give us an idea of what we were supposed to generate. This was very helpful.

Patrick Regan, Software Programmer, MGHPCC

I can definitely apply what I have learned as I need to create some graphs for usage of our archive.

Adil Hasan, Owner, DataTailor Ltd
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