Mastering Data Visualization
Intermediate
4.6
1021 reviews
15k+ Learners
This track helps master key data visualization techniques. It covers NumPy and Pandas for data preparation and processing, Python libraries for creati…
150
Chapters
16
Learning hours
146
Assignments
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What you will learn
Creating and manipulating NumPy arrays
Performing math operations with NumPy
Visualizing data with Matplotlib
Indexing and slicing NumPy arrays
Creating and manipulating pandas DataFrames
Building interactive reports in Power BI
Applying common NumPy functions
Handling missing values in pandas
Creating dynamic visualizations in Tableau
Learning track content
Explore the applications of NumPy and understand why it's one of the most popular libraries for numerical computing. Learn the different ways to create and initialize arrays to handle various data needs efficiently.
Discover how to access specific elements and subsets in NumPy arrays using index notation. Learn to apply conditional indexing to filter data and manage missing values efficiently.
NumPy provides many built-in functions for performing common array operations. Learn how to apply these tools to transform, aggregate, and analyze data efficiently without writing repetitive code.
Learn how to perform mathematical operations efficiently on NumPy arrays. Apply these operations to solve real-world problems and gain a deeper understanding of how vectorized computations speed up numerical analysis.
Dive into the fundamentals of the pandas library. Learn to create and manipulate Series and DataFrames, explore their structure, and build confidence in performing essential data operations.
Master how to load and manage data from CSV and TXT files. Gain practical experience importing datasets and preparing them for further analysis using pandas tools.
Learn to explore, clean, and summarize data effectively. Understand how to handle missing values, extract insights, and perform basic statistical operations with pandas.
Viewing the Data
Quiz: Using head()
Quiz: head(), tail(), and sample()
Exploring the Dataset
Column Names and Data Types
Finding Null Values
Quiz: Identifying Null Values
Challenge: Dropping Null Values
Challenge: Filling Null Values
Quiz: Null Values
Describing the Data
max() and min()
Quiz: Statistical Operations
sum() and count()
Unique Values
Discover the essentials of data visualization with Matplotlib. Learn its core concepts, explore its advantages, and create your first simple plot using this fundamental plotting library.
Master how to visualize data through the most popular plot types. Learn to build line, scatter, and bar charts to clearly communicate insights from your data.
Learn to make your plots more informative and visually appealing. Add titles, legends, colors, and grids, and discover how to arrange multiple subplots effectively.
Take your visualization skills to the next level with Seaborn. Create advanced plots like countplots, KDEs, pair plots, and heatmaps while mastering Seaborn’s elegant style and customization options.
Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.
Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.
Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.
Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.
Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.
This section lays the groundwork for mastering Tableau by guiding you through installation, navigation, and foundational operations. From performing joins and splitting columns to understanding filters, marks, and the data pane, you will be equipped with essential tools for data exploration and visualization.
This section delves into Tableau's powerful tools for data organization, filtering, and customization. You'll learn to differentiate dimensions and measures, work with continuous and discrete fields, and create calculated fields and interactive dashboards. Through practical challenges, you'll apply these tools to analyze data, uncover insights, and enhance your visualizations.
Dimensions and Measures
Challenge: Comparing Sales and Profit by State
Continuous and Discrete Fields
Challenge: Identifying the Month with Lowest Sales
Dimension Filters
Measure Filters
Challenge: Finding the Most Profitable Customer in Art
Calculated Fields
Challenge: Comparing California and New York to Other States
Interactive Dashboards with Parameters
Challenge: Finding the Sub-Category with the Most Sales
Working with Sets
Challenge: Analyzing Bookcase Profit Concentration
Sets Applications
This section focuses on creating impactful visualizations to uncover patterns and trends in your data. From heatmaps and scatter plots to treemaps and combination charts, you'll explore a variety of chart types tailored to different analytical needs.
Visualizing Data with Heatmaps
Challenge: Identifying Top-Selling Sub-Category by Region
Scatter Plots
Challenge: Determining the Highest Sales and Profit by State
Treemaps
Challenge: Analyzing the Least Profitable Sub-Category
Combination Charts
Challenge: Comparing Sales and Profit Trends for Phones
Sparklines
This section introduces advanced visualization techniques to enhance data analysis and storytelling. You'll learn to create bullet graphs, stacked area charts, histograms, and box plots, enabling deeper insights into trends, distributions, and comparisons.
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