Python for Data Analysis & Visualization
- 06:26 Hours
- 20 Lectures
- 1 Student Enrolled
Analyze data, uncover insights, and create powerful visualizations using Python and popular libraries.
Course Overview
This course is designed to help you use Python for real-world data analysis. You will learn how to clean, analyze, and visualize data using industry-standard tools like NumPy, Pandas, and Matplotlib.
Through hands-on examples and practical exercises, you will work with real datasets and build charts, graphs, and reports that tell meaningful stories from data.
By the end of the course, you will be able to confidently perform data analysis tasks and present insights visually.
What You Will Learn
- Installing Python and IDEs
- Basic Python Syntax
- Introduction to Pandas Series
- Pandas DataFrames Basics
- Introduction to Matplotlib
- Scatter Plots and Bar Charts
- Customizing Axes and Labels
- Exporting High-Quality Plots
- Handling Missing Values
- Filtering and Sorting Data
- Data Grouping (GroupBy)
- Merging and Joining DataFrames
- Introduction to Seaborn
- Heatmaps and Correlation
- Interactive Plots with Plotly
- Dashboarding Basics
- Project Overview and Scope
- Data Ingestion and Cleaning
- Exploratory Data Analysis (EDA)
- Final Presentation and Insights
Course Curriculum
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Installing Python and IDEs Preview 00:15:30
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Basic Python Syntax 00:20:15
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Introduction to Pandas Series 00:18:00
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Pandas DataFrames Basics 00:25:40
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Introduction to Matplotlib Preview 00:12:00
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Scatter Plots and Bar Charts 00:15:30
-
Customizing Axes and Labels 00:18:15
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Exporting High-Quality Plots 00:10:45
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Handling Missing Values Preview 00:15:00
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Filtering and Sorting Data 00:19:30
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Data Grouping (GroupBy) 00:21:15
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Merging and Joining DataFrames 00:26:00
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Introduction to Seaborn Preview 00:14:40
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Heatmaps and Correlation 00:17:20
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Interactive Plots with Plotly 00:22:10
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Dashboarding Basics 00:19:50
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Project Overview and Scope Preview 00:10:00
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Data Ingestion and Cleaning 00:28:30
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Exploratory Data Analysis (EDA) 00:35:15
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Final Presentation and Insights 00:20:45
Akash Prajapati
- 5
- 20 Lectures
- 5 Students Enrolled
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Course FAQ's
You should understand basic Python syntax (loops, variables, lists) before starting the data analysis modules.
Yes, these two libraries form the core of the course for data manipulation and mathematical operations.
We primarily use Jupyter Notebooks, which are standard in the data science industry.
No, this course focuses on cleaning, analyzing, and visualizing data, which is the necessary step right before machine learning.
$399.00
Analyze data, uncover insights, and create powerful visualizations using Python and popular libraries.
- 3.0 Rating
- 06:26
- 1 Student Enrolled
- 20 Lectures
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