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Big Data Analytics

Data Visualization with Matplotlib & Seaborn

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  • Overview

    Matplotlib is a data visualization library for Python. As part of the SciPy data analysis library it is widely used to create data graphics. However, Matplotlib is older than the pandas library, the most common Python library for data frame manipulation. The Matplotlib library requires some extra steps when plotting data from pandas data frames that sometimes make it more cumbersome to use. Seaborn was created to address some of those issues. Seaborn presents more natural default settings and works with pandas data frames directly. Both libraries should be in a data analyst’s tool box.

    Topics covered include:

    • Matplotlib features and functions
    • Seaborn features and functions
    • When to use Matplotlib vs. Seaborn
    • Customizing graphs
    • Visualizing relationships in data
  • Who Should Take This Course

    Audience

    This course is suitable for any student that wants a quick introduction to visualizing and extracting meaning from data.

    PREREQUISITES

    Students taking this course should have the following skills:

    • Basic Python programming skills (Python for Data Science)
    • Basic command line experience on Linux, Windows, or Mac
  • Why You Should Take This Course

    At the end of the course students will be able to:

    • Customize plots
    • Plot 2D arrays
    • Create plots with Seaborn
    • Create line graphs
    • Create bar charts
    • Create pie charts
    • Add error bars, labeling, and styling to graphs

    This training prepares individuals for the following positions:

    • Data engineer, Data analyst, Data architect, Data scientist, Software engineer
  • Schedule
  • Course Outline

    SQL

    • RDBMS Basics and Concepts
    • SQL Basics and Review with PostgreSQL
    • Logical operators and Arithmetic operators
    • Data cleaning and scrubbing with SQL
    • SQL Functions
    • Importing and Exporting Data

    Data Analysis with Excel

    • Basic spreadsheet operations
    • Importing Data: CSV, Fixed width text
    • Absolute vs. relative references
    • Functions
    • Lookups: VLOOKUP, HLOOKUP
    • Data Filtering
    • Pivot Tables
    • Excel Chart Basics

    Data Analysis with Python

    • Python Basics
    • Overview of Python Packages for Data Analysis
    • NumPy, Pandas, SciPy, SciKit-Learn
    • Overview of Python Packages for Visualization
    • Matplotlib, Seaborn
    • Reading Excel data into Pandas
    • Exploring Data Frames
    • Data Frame data types
    • Data Frame attributes
    • Selecting Data
    • Slicing Data
    • Filtering Data
    • Sorting Data
    • Grouping Data
    • Aggregate Functions and Descriptive Statistics
    • Plotting Data and Graphs

    Putting it Together with PowerPoint

    • Graphing in PowerPoint
    • Adding graphs from other sources
  • FAQs
    Is there a discount available for current students?

    UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Online courses are excluded from this offer.

    What is the cancellation and refund policy?

    Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.

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