Section 1: Data Analysis Essentials Page 18
In this section, we will learn how to speak the language of data by extracting useful and actionable insights from data using Python and Jupyter Notebook. We'll begin with the fundamentals of data analysis and work with the right tools to help you analyze data effectively. After your workspace has been set up, we'll learn how to work with data using two popular open source libraries available in Python: NumPy and pandas. This will lay the foundation for you to understand data so that you can prepare for Section 2: Solutions for Data Discovery.
- The section 1 includes the following topics:
- Fundamentals of Data Analysis
- Overview of Python and Installing Jupyter Notebook
- Getting Started with NumPy
- Creating Your First pandas DataFrame TP1 :
- Gathering and Loading Data in Python TP2 :
- pandas cheat sheet 1
- pandas cheat sheet 2
Section 2: Solutions for Data Discovery Page 123
In this section, we'll learn how to visualize data for analysis by working with time series data. Then, we'll learn how to clean and join multiple datasets together using both SQL and DataFrames with Python. After that, we'll go back to data visualization and learn about the best practices when it comes to data storytelling. By the end of this section, you will understand the foundations of descriptive analytics.
- The section 2 includes the following topics:
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Exploratory data analysis TP3 :
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Visualization with
matplotlib: -
Visualizing and Working with Time Series Data
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Exploring, Cleaning, Refining, and Blending Datasets TP4 :
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Understanding Joins, Relationships, and Aggregates
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Plotting, Visualization, and Storytelling
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Project template for
COVID 19dataset :
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