Data Understanding and Data Visualization with Python [Video]
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-
Free ChapterIntroduction to the Course
-
Strings in Python
-
Python Data Structure
- Introduction to Data Structure
- Data Structures - Defining and Indexing
- Data Structures - Insertion and Deletion
- Data Structures-Insertion and Deletion Quiz
- Data Structures-Insertion and Deletion Solution
- Data Structures - Insertion and Deletion Python Practice
- Data Structures-Insertion and Deletion Python Practice Quiz
- Data Structures insertion And Deletion python Practice Solution
- Data Structures - Deep Copy or Reference and Slicing
- Data Structures-Deep Copy or Reference and Slicing Quiz
- Data Structures-Deep Copy or Reference and Slicing Solution
- Data Structures - Exploring Methods Using TAB Completion
- Data Structures - Abstract Ways
- Data Structures - Problem Solving Practice
- Data Structures Problem Solving Practice Quiz
- Data Structures-Problem Solving Practice Solution
-
NumPy for Numerical Data Processing
- Introduction to NumPy
- NumPy Dimensions
- NumPy Shape, Size, and Bytes
- NumPy Arange and Random Package
- NumPy Arange and Random Package Quiz
- NumPy Arange and Random Package Solution
- NumPy Random and Reshape
- NumPy Slicing Combined
- NumPy Slicing Combined Quiz
- NumPy Slicing Combined Solution
- NumPy Masking
- NumPy Masking Quiz
- NumPy Masking Solution
- NumPy Broadcasting and Concatenation
- NumPy Ufuncs and SpeedTest
- Ufuncs Add, Sum, and Plus Operators
- Ufuncs Subtract Power Mod
- Ufuncs Comparisons Logical Operators
- Ufuncs Comparisons Logical Operators Quiz
- Ufuncs Comparisons Logical Operators Solution
- Ufuncs Output Argument
- NumPy Playing with Images
- NumPy Playing With Images Quiz
- NumPy Playing With Images Solution
- NumPy KNN Classifier from Scratch
- NumPy Structured Arrays
- NumPy Structured Arrays Quiz
- NumPy Structured Arrays Solution
-
Pandas for Data Manipulation and Understanding
- Introduction to Pandas
- Pandas Series
- Pandas DataFrame
- Pandas DataFrame Quiz
- Pandas DataFrame Solution
- Pandas Missing Values
- Pandas loc and Iloc
- Pandas in Practice
- Pandas Group By
- Pandas Group By Quiz
- Pandas Group By Solution
- Hierarchical Indexing
- Pandas Rolling
- Pandas Rolling Quiz
- Pandas Rolling Solution
- Pandas Where
- Pandas Clip
- Pandas Clip Quiz
- Pandas Clip Solution
- Pandas Merge
- Pandas Merge Quiz
- Pandas Merge Solution
- Pandas Pivot Table
- Pandas Strings
- Pandas DateTime
- Pandas Hands-On COVID-19 Data
- Pandas Hands-On COVID-19 Data Bug Fixed
-
Matplotlib for Data Visualization
- Introduction to Matplotlib
- Matplotlib Multiple Plots
- Matplotlib Colors and Styles
- Matplotlib Colors and Styles Quiz
- Matplotlib Colors and Styles Solution
- Matplotlib Colors and Styles Shortcuts
- Matplotlib Axis Limits
- Matplotlib Axis Limits Quiz
- Matplotlib Axis Limits Solution
- Matplotlib Legends Labels
- Matplotlib Set Function
- Matplotlib Set Function Quiz
- Matplotlib Set Function Solution
- Matplotlib Markers
- Matplotlib Markers Random Plots
- Matplotlib Scatter Plot
- Matplotlib Contour Plot
- Matplotlib Contour Plot Quiz
- Matplotlib Contour Plot Solution
- Matplotlib Histograms
- Matplotlib Subplots
- Matplotlib Subplots Quiz
- Matplotlib Subplots Solution
- Matplotlib 3D Introduction
- Matplotlib 3D Scatter Plots
- Matplotlib 3D Scatter Plot Quiz
- Matplotlib 3D Scatter Plot Solution
- Matplotlib 3D Surface Plots
-
Seaborn for Data Visualization
-
Bokeh for Interactive Plotting
-
Plotly for 3D Interactive Plotting
-
Geographic Maps with Folium
-
Pandas for Plotting
About this
video
Data visualization has gained a lot of traction resulting from an increased focus on data analytics. To be a successful data scientist, data manipulation and wrangling are not enough. Visualizing data to garner insights is an equally important tool in the data science toolkit. Given the myriad types of data that exist, visualization has become an increasingly important topic.
This course will equip you with all the skills you need to successfully create insightful visualizations. The course first starts with the fundamentals of Python. Then, the course teaches you how to use libraries such as NumPy, Pandas, Matplotlib, Seaborn, Bokeh, and so on. Additionally, you will learn data manipulation, which is the step prior to visualization. You will also learn how to plot geographical data using Folium. Each module in the course has practical hands-on mini projects, and with the mammoth content, this is one of the most comprehensive courses you will be doing on data visualization in Python.
By the end of this course, you have not only learned the theoretical fundamentals of visualizations but also gained essential practical skills to explore this growing domain.
The code files and all related files are uploaded on GitHub at: https://github.com/PacktPublishing/Data-Understanding-and-Data-Visualization-with-Python
- Publication date:
- March 2021
- Publisher
- Packt
- Duration
- 15 hours 13 minutes
- ISBN
- 9781801078795