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This plan includes
- Access to 11,000+ Courses
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HD Video Recorded Lectures- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
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- Email & Chat Support
- Cancel Anytime
What you'll learn?
- Best practices from pandas expert Ted Petrou author of Master Data Analysis with Python
- Introduction to the pandas DataFrame and Series
- Understanding the different data types available within a DataFrame
- Accessing the DataFrame components - the index, columns, and values
- Setting a meaningful index in a DataFrame
- Completing a five-step process for data exploration
Course Overview
Master Data Analysis with Python - Intro to Pandas targets those who want to completely master doing data analysis with pandas. This course provides an introduction to the two primary pandas objects, the DataFrame and Series. This is a brand new free course updated for the latest version of pandas.
This course is taught by expert instructor Ted Petrou, author of the highly-rated textbooks Pandas Cookbook and Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.
All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place.
This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis in a professional environment.
Intro to Pandas is first in the Master Data Analysis with Python series which includes the following sequence of courses:
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Intro to Pandas
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Selecting Subsets of Data with Pandas
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Essential Pandas Commands
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Grouping Data with Pandas
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Time Series with Pandas
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Cleaning Data with Pandas
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Joining Data with Pandas
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Data Visualization
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Advanced Pandas
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Exploratory Data Analysis
This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.
Pre-requisites
- It is necessary to understand the fundamentals of the Python programming language. No prior experience with pandas needed.
Target Audience
- Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data
Curriculum 28 Lectures 01:26:56
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Section 1 : Introduction
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Section 2 : Course Contents
- Lecture 1 :
- Downloading the Course Material
- Lecture 2 :
- Exploring the Course Contents
- Lecture 3 :
- Opening the Material with Jupyter Notebooks
- Lecture 4 :
- Working through a Course Material
- Lecture 5 :
- Differences with Video Notebooks
- Lecture 6 :
- When to Open a New Notebook
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Section 3 : What is pandas?
- Lecture 1 :
- What is pandas?
- Lecture 2 :
- Which version of pandas to use?
- Lecture 3 :
- Pandas examples
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Section 4 : The DataFrame and Series
- Lecture 1 :
- Intro to the DataFrame and Series
- Lecture 2 :
- DataFrame Components
- Lecture 3 :
- Selecting a Series
- Lecture 4 :
- Components of a Series
- Lecture 5 :
- Getting Help in a Jupyter Notebook
- Lecture 6 :
- Exercises
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Section 5 : Data Types and Missing Values
- Lecture 1 :
- Intro to Data Types and Missing Values
- Lecture 2 :
- Finding the Data Type of Each Column
- Lecture 3 :
- Getting More Metadata
- Lecture 4 :
- Exercises
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Section 6 : Setting an Index of a DataFrame
- Lecture 1 :
- Setting an Index of a DataFrame
- Lecture 2 :
- Accessing the Index, Columns, and Data
- Lecture 3 :
- Accessing the Components of a Series
- Lecture 4 :
- The Default Index
- Lecture 5 :
- Setting an Index on Read
- Lecture 6 :
- Choosing a Good Index
- Lecture 7 :
- Exercises
-
Section 7 : Five-Step Process for Data Exploration
- Lecture 1 :
- Five-Step Process for Data Exploration
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Frequently Asked Questions
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How do i access the course after purchase?
It's simple. When you sign up, you'll immediately have unlimited viewing of thousands of expert courses, paths to guide your learning, tools to measure your skills and hands-on resources like exercise files. There’s no limit on what you can learn and you can cancel at any time. -
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Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic. -
Can i play & pause the course as per my convenience?
Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on. -
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Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want. -
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Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly. -
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