This advanced Pandas course delves deep into date-time manipulation, covering Timestamps, DatetimeIndex objects, and pd.date_range for effective time series handling.
Advanced Data Analysis and Visualization with Pandas
Advanced Data Analysis and Visualization with Pandas
This course is part of Data Analysis with Pandas and Python Specialization
Instructor: Packt - Course Instructors
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Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Demonstrate proficiency in exporting and importing data in CSV and Excel formats using Pandas.
Create and customize data visualizations using Matplotlib to effectively present insights.
Adjust Pandas settings and parameters to optimize data analysis for specific needs.
Apply advanced Pandas techniques to streamline data workflows and improve efficiency in data handling and analysis.
Skills you'll gain
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Recently updated!
August 2024
Assessments
6 assignments
Taught in English
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This course is part of the Data Analysis with Pandas and Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
In this module, we will explore how to handle dates and times in Pandas, starting with an introduction to the concepts and a review of Python's datetime module. You will learn to utilize Timestamp and DatetimeIndex objects for manipulating date-time data and create ranges of dates using the pd.date_range function. We will cover accessing date and time properties using the dt attribute, selecting DataFrame rows based on date-time indexes, and performing time-based arithmetic operations with the DateOffset object. Additionally, you'll master specialized date offsets and understand the concept of timedeltas for representing durations of time.
What's included
8 videos2 readings1 assignment
In this module, we will explore input and output operations in Pandas, starting with an overview of essential data exchange techniques. You will learn how to export DataFrames to CSV files, a common format for data sharing. We will guide you through installing the openpyxl library to enable reading and writing Excel files in Pandas. Additionally, you'll master importing data from Excel files into Pandas and exporting DataFrames to Excel for effective data reporting and sharing.
What's included
5 videos1 assignment
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.
What's included
5 videos1 assignment
In this module, we will explore how to customize Pandas' behavior and output through various options and settings. You will learn to change Pandas options using attributes, adjusting settings to suit different analysis needs. We will also cover how to change options using functions, providing greater flexibility and control over your data analysis environment. Additionally, you'll understand the precision option to control the output display precision of floating-point numbers, ensuring data clarity and readability.
What's included
4 videos1 assignment
In this module, we will wrap up the course by summarizing the key concepts and techniques you've learned. We'll reinforce the comprehensive skill set you have acquired in data analysis with Pandas and Python, providing final insights and encouragement for your continued learning and application of these skills in real-world scenarios.
What's included
1 video1 reading2 assignments
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Northeastern University
University of Michigan
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.