Embark on a comprehensive journey into data analysis with Python and Pandas. Learn to set up Anaconda and Jupyter Lab on macOS and Windows, navigate Jupyter Lab's interface, and execute code cells.
Foundations of Data Analysis with Pandas and Python
Foundations of Data Analysis with Pandas and Python
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.
Beginner level
Recommended experience
9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Explain how to navigate and utilize Jupyter Lab for Python programming.
Write Python code, including functions and data structures.
Manipulate and analyze data using Pandas Series and DataFrames.
Apply data cleaning and sorting techniques to prepare datasets for analysis.
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Recently updated!
August 2024
Assessments
4 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 3 modules in this course
In this module, we will guide you through the initial setup required for this course, including installing the Anaconda distribution on both macOS and Windows, and creating Python environments using Anaconda Navigator. You'll also learn to unpack the provided course materials, navigate the Jupyter Lab interface, execute code cells, and import necessary libraries to get you started on your data analysis journey.
What's included
8 videos2 readings1 assignment
In this module, we will cover the essentials of Python programming, starting with the use of comments to enhance code readability. You'll gain familiarity with Python's basic data types, operators, variables, and built-in functions, laying the groundwork for effective coding. We will delve into custom functions, string methods, lists, indexing and slicing, dictionaries, and classes to build your programming skills. Finally, you will learn to navigate and use Python libraries within Jupyter Lab, a critical skill for data analysis.
What's included
12 videos1 assignment
In this module, we will explore the creation and manipulation of Pandas Series objects from different data sources like lists and dictionaries. We will delve into essential methods and attributes of Series, understand the use of parameters and arguments, and learn techniques to import data into Series using 'pd.read_csv'. Additionally, we will cover methods for inspecting, sorting, and extracting Series values, along with advanced operations like broadcasting and applying functions to Series elements.
What's included
21 videos1 reading2 assignments
Instructor
Offered by
Recommended if you're interested in Data Analysis
Coursera Project Network
University of Colorado Boulder
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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.