uCertify

Data Visualization and Exploratory Data Analysis

(CTU-AI340.AP1)
Lessons
Lab
AI Tutor (Add-on)
Get A Free Trial

Skills You’ll Get

Download Course Outline

1

Handling Missing Data and Outliers

  • Technical requirements
  • Line chart
  • Bar charts
  • Scatter plot
  • Area plot and stacked plot
  • Pie chart
  • Table chart
  • Polar chart
  • Histogram
  • Lollipop chart
  • Choosing the best chart
  • Other libraries to explore
  • Technical requirements
  • Understanding statistics
  • Measures of central tendency
  • Measures of dispersion
  • Technical requirements
  • Introducing correlation
  • Types of analysis
  • Discussing multivariate analysis using the Titanic dataset
  • Outlining Simpson's paradox
  • Correlation does not imply causation
2

Understanding Data Distributions with Descriptive Statistics

  • Combine Data Sets
  • Concatenation
  • Observational Units Across Multiple Tables
  • Merge Multiple Data Sets
  • Conclusion
  • What Is a NaN Value?
  • Where Do Missing Values Come From?
  • Working With Missing Data
  • Pandas Built-In NA Missing
  • Conclusion
  • Data Types
  • Converting Types
  • Categorical Data
  • Conclusion
3

Dimensionality Reduction Techniques

  • Simple Linear Regression
  • Multiple Regression
  • Models with Categorical Variables
  • One-Hot Encoding in scikit-learn with Transformer Pipelines
  • Conclusion
  • About This Lesson
  • Logistic Regression (Binary Outcome Variable)
  • Poisson Regression (Count Outcome Variable)
  • More Generalized Linear Models
  • Conclusion
  • k-Means
  • Hierarchical Clustering
  • Conclusion
  • Technical requirements
  • Types of machine learning
  • Understanding supervised learning
  • Understanding unsupervised learning
  • Understanding reinforcement learning
  • Unified machine learning workflow
4

Building Visualizations with Python

  • Introduction
  • Handling Data with pandas DataFrame
  • Plotting with pandas and seaborn
  • Tweaking Plot Parameters
  • Introduction
  • Creating Plots that Present Global Patterns in Data
  • Creating Plots That Present Summary Statistics of Your Data
  • Introduction
  • Static versus Interactive Visualization
  • Applications of Interactive Data Visualizations
  • Getting Started with Interactive Data Visualizations
5

Advanced Data Cleaning and Outlier Analysis

  • Introduction
  • Interactive Scatter Plots
  • Other Interactive Plots in altair
  • Introduction
  • Temporal Data
  • Types of Temporal Data
  • Understanding the Relation between Temporal Data and Time-Series Data
  • Examples of Domains That Use Temporal Data
  • Visualization of Temporal Data
  • Choosing the Right Aggregation Level for Temporal Data
  • Resampling in Temporal Data
  • Interactive Temporal Visualization
  • Introduction
  • Data Formatting and Interpretation
  • Data Visualization
  • Cheat Sheet for the Visualization Process

1

Handling Missing Data and Outliers

  • Creating a Line chart
  • Creating a Bar Chart
  • Creating a Scatter Plot
  • Creating a Bubble Chart
  • Creating an Area Plot
  • Creating a Pie Chart
  • Creating a Table Chart
  • Creating a Polar Chart
  • Adding the Best-Fit Line for the Normal Distribution
  • Creating a Histogram
  • Creating a Lollipop Chart
  • Generating a Binomial Distribution Plot
  • Generating an Exponential Distribution Plot
  • Generating a Normal Distribution Plot
  • Generating a Uniform Distribution Plot
  • Using Statistical Functions
  • Calculating Standard Deviation
  • Finding Skewness and Kurtosis
  • Creating a Box Plot
  • Calculating Inter-Quartile Range
  • Calculating Correlation Coefficient
2

Understanding Data Distributions with Descriptive Statistics

  • Performing Concatenation Using the concat() Function
  • Merging Multiple Data Sets Using the .merge() Function
  • Finding and Cleaning Missing Data
  • Performing Data Type Conversion
3

Dimensionality Reduction Techniques

  • Performing Linear Regression
  • Performing Multiple Regression
  • Performing Logistic Regression
  • Performing Poisson Regression Using the poisson() Function
  • Performing k-Means Clustering
  • Using Hierarchical Clustering Algorithms
  • Using TfidfVectorizer
4

Building Visualizations with Python

  • Creating a User-defined Function
  • Applying the ceil() Function on a DataFrame Column
  • Adding a Column to a DataFrame
  • Applying the describe() Function
  • Viewing Data from Dataset
  • Deleting Columns from a DataFrame
  • Reading Data from a File
  • Creating a Bar Plot and Calculating the Mean Growth Rate Distribution
  • Creating Bar Plot Grouped by a Specific Feature
  • Plotting a Histogram
  • Tweaking the Plot Parameters of a Grouped Bar Plot
  • Annotating a Bar Chart
  • Presenting Data across Time with Multiple Line Plots
  • Creating a Static Line Plot
  • Creating a Static Hexagonal Binning Plot
  • Creating a Static Scatter Chart
  • Creating a Static Contour Plot
  • Creating a Static Heatmap
  • Creating a Linkage in a Static Heatmap
  • Creating a Static Box Plot
  • Creating a Static Violin Plot
  • Creating the Base Static Plot for Interactive Data Visualization
  • Adding a Slider to the Static Plot
  • Adding a Hover Tool to a Scatter Plot Using bokeh
  • Creating an Interactive Scatter Plot
  • Using the merge() function
5

Advanced Data Cleaning and Outlier Analysis

  • Adding Zoom-In and Zoom-Out to a Static Scatter Plot Using altair
  • Adding Hover and Tooltip Functionality to a Scatter Plot Using altair
  • Exploring Select and Highlight Functionality on a Scatter Plot Using altair
  • Performing Selection across Multiple Plots
  • Performing a Selection Based on the Values of a Feature
  • Adding the Zoom Feature and Calculating the Mean on a Static Bar Plot
  • Representing the Mean on a Bar Plot using a Shortcut
  • Linking a Bar Plot and a Heatmap Dynamically
  • Adding a Zoom Feature on a Static Heatmap
  • Creating a Bar Plot and a Heatmap Next to Each Other
  • Calculating zscore to Find Outliers in Temporal Data
  • Performing Upsampling and Downsampling in Temporal Data
  • Using shift and tshift to Shift Time in Data
  • Adding Zoom-in and Zoom-out Functionality on a Line Plot Using Bokeh
  • Adding Interactivity to Static Line Plots using Bokeh
  • Changing the Line Color and Width on a Line Plot
  • Adding Box Annotations to Find Anomalies in a Dataset
  • Visualizing Outliers in a Dataset with a Box Plot
  • Dealing with Outliers
  • Dealing with Missing Values
  • Creating a Confusing Visualization

Any questions?
Check out the FAQs

Still have unanswered questions and need to get in touch?

Contact Us Now

Related Courses

All Courses
We use cookies for improving site experience and analytics. Learn More