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Python Data Analysis

This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data.

By the end of the course, you will be comfortable working with tabular data in Python. This will extend your Python programming expertise, enabling you to write a wider range of scripts using Python.

This course uses Python 3. While most Python programs continue to use Python 2, Python 3 is the future of the Python programming language. This course uses basic desktop Python development environments, allowing you to run Python programs directly on your computer.

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What's inside

Syllabus

Dictionaries

This module will teach you about Python's dictionary data type and its capabilities. Dictionaries are used to map keys to values within programs.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers Python 3, which is the future of Python

Examines working with tabular data, which is common in industry

Teaches dictionaries, tabular data, and CSV files, which are core to Python programming

Develops Python programming expertise, which is useful in a variety of settings

Strengthens existing foundations in Python programming

Taught by Scott Rixner and Joe Warren, who are recognized for their work in Python

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Reviews summary

Foundational python for basic data handling

According to students, this course provides a solid foundation in using basic Python structures like lists and dictionaries for handling tabular data and CSV files. While the course is titled "Data Analysis", many students note that it doesn't cover standard modern data analysis libraries like Pandas or NumPy. This makes it good for absolute beginners but potentially limited or misleading for those expecting to learn contemporary data analysis techniques.

Covers dictionaries, lists, CSVs, sorting.

"The modules on dictionaries and CSV file handling were particularly useful."

"Learned how to organize and sort data using Python's built-in functions."

"Provided good coverage of lists and dictionaries for storing data."

Great start for beginners.

"This course gave me a solid foundation in Python for data."

"Excellent introduction if you are new to handling data with Python."

"Perfect for understanding basic data structures and CSV handling."

Pace can be slow for some learners.

"The pace felt quite slow at times."

"Would recommend speeding up some of the earlier modules."

"Good slow pace for absolute beginners, but others might find it tedious."

Missing key modern data tools like Pandas.

"I was disappointed it didn't cover Pandas or NumPy."

"The title 'Data Analysis' is misleading without modern libraries."

"Good basics, but not what I expected for actual data analysis workflows."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Data Analysis with these activities:

Review Python Basics Before Starting the Course

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If you have some experience with Python, this activity will help you brush up on the basics before starting the course.

Browse courses on Python Basics

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Review the Python documentation.
Take a Python practice test.
Complete a few Python coding exercises.

Follow a Python Tutorial Series

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Following a tutorial series can help you learn the basics of Python and get up to speed quickly.

Browse courses on Python

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Choose a tutorial series that is appropriate for your skill level.
Follow the tutorials in the series and complete the exercises.
Create a small Python program that you can use to solve a problem in your life.

Create a Python Study Guide

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Creating a study guide can help you organize your notes and prepare for the course.

Browse courses on Python Programming

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Compile notes from the class lectures.
Review the Python documentation and add any important information to your notes.
Organize your notes into a logical format.

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Read Introduction to Python Programming

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This book provides a quick and easy way to learn the basics of Python without having to know anything about programming.

View Introduction to Computation and Programming... on Amazon

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Read Chapters 1-3.
Complete the exercises at the end of each chapter.
Create a small Python program that you can use to solve a problem in your life.

Join a Python Study Group

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Joining a study group can help you stay motivated and learn from others.

Browse courses on Python Programming

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Find a study group that meets regularly.
Attend the study group meetings.
Participate in discussions and ask questions.

Practice Python Coding Exercises

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Practice is key to learning Python. These exercises can help you master the basics and improve your skills.

Browse courses on Python Coding

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Find a set of Python coding exercises (such as those on LeetCode).
Attempt to solve the exercises on your own.
Review the solutions to the exercises to see how you can improve your approach.

Write a Blog Post or Article on Python

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Writing about what you learn is a great way to reinforce your understanding and share your knowledge with others.

Browse courses on Python Programming

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Choose a topic that you are familiar with.
Research the topic to make sure you have a good understanding of it.
Write a blog post or article that explains the topic in a clear and concise way.

Contribute to an Open Source Python Project

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Contributing to open source projects can help you learn how to work with others and make a real-world impact.

Browse courses on Python Programming

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Find an open source Python project that you are interested in.
Read the project documentation and start contributing to the project.
Submit pull requests to the project and work with others to improve the project.

Career center

Learners who complete Python Data Analysis will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their programming skills to analyze data. They often must read and understand large amounts of tabular data, and reshape the data into different formats. This course teaches the basics of working with tabular data in Python, which is one of the most popular programming languages for data analysis. This course will teach you how to overcome obstacles that can occur while trying to read, store, and process tabular data, which will make you a more effective Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts often partner with Data Analysts. Both roles collect and analyze data, but Business Analysts typically focus on the business side of data from a high level. This course provides a foundation in working with tabular data, which will be useful to a Business Analyst who wants to understand data in more detail.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists are similar to Data Analysts, but they typically deal with much more complex problems and are often expected to build predictive models. This course is a useful introduction to reading and writing tabular data in Python, which are important skills for Data Scientists.

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Software Engineer

Software Engineers develop and maintain software products. While Software Engineers do not typically analyze data in the same way as Data Analysts or Data Scientists, they do often need to work with tabular data. This course can help you build a foundation in working with tabular data in Python, which is a valuable skill for Software Engineers.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers build and maintain the infrastructure that allows Data Analysts and Data Scientists to do their jobs. This course can be helpful in building a foundation in working with tabular data in Python.

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Statistician

Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. This course can help you build a foundation in working with tabular data in Python, which is useful for Statisticians.

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Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. This course can be helpful in building a foundation in working with tabular data in Python, which is useful for reading and analyzing financial data.

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Actuary

Actuaries use mathematical and statistical methods to assess risk in the insurance and finance industries. This course can help you build a foundation in working with tabular data in Python, which is a valuable skill for Actuaries.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical methods to solve problems in a variety of industries. This course can help you build a foundation in working with tabular data in Python, which is a useful skill for Operations Research Analysts.

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Market Researcher

Market Researchers collect and analyze data about consumers and markets. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Market Researchers who analyze large amounts of data.

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Epidemiologist

Epidemiologists investigate the causes of disease and other health problems in populations. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Epidemiologists who analyze large amounts of data.

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Biostatistician

Biostatisticians apply statistical methods to data in the biological sciences. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Biostatisticians who analyze large amounts of data.

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Data Journalist

Data Journalists use data to tell stories. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Data Journalists who analyze large amounts of data.

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UX Researcher

UX Researchers study how users interact with products and services. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for UX Researchers who analyze large amounts of data.

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Product Manager

Product Managers are responsible for the development and success of products. This course can be helpful in building a foundation in working with tabular data in Python, which can be useful for Product Managers who analyze large amounts of data.

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Reading list

We've selected 18 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python Data Analysis.

Python for Data Analysis

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Provides a comprehensive overview of data analysis in Python, covering topics such as data cleaning, exploration, and visualization. It valuable resource for anyone looking to learn more about data analysis in Python.

Python Data Analysis

What's inside

Syllabus

Traffic lights

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Reviews summary

Foundational python for basic data handling

Activities

Career center

Reading list

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