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Packt

Advanced Data Analysis and Visualization with Pandas

Course 3 of 3 in the Data Analysis with Pandas and Python Specialization

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This advanced Pandas course delves deep into date-time manipulation, covering Timestamps, DatetimeIndex objects, and pd.date_range for effective time series handling. - You'll master techniques like using the dt attribute and DateOffset objects for arithmetic operations and timedeltas. - Learn essential input-output operations, including exporting DataFrames to CSV and Excel files using openpyxl, and seamless file imports. - Enhance data presentation with Matplotlib for basic visualizations, customizing aesthetics with templates, and creating bar and pie charts. Ideal for data analysts, scientists, and Python enthusiasts with intermediate to advanced Pandas skills, this course enriches data workflows and visualization capabilities.

Skills You'll Learn

Data Analysis, Pandas (Python Package), Time Series Analysis and Forecasting, Data Manipulation, Matplotlib, NumPy, Data Import/Export, Python Programming, Microsoft Excel, Data Visualization Software

From the lesson

Visualization

In this module, we will delve into data visualization techniques using Pandas and Matplotlib. You will begin with installing the Matplotlib library, a crucial tool for creating diverse visualizations in Python. We will explore the plot method in Pandas for basic line plots and demonstrate how to modify plot aesthetics using templates. Additionally, you'll learn to create bar charts for comparing groups or tracking changes over time, and construct pie charts to effectively display proportions of a whole.

Install matplotlib Library for Visualization1:52

The plot Method6:39

Modifying Plot Aesthetics with Templates4:25

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