Data Analysis in Python with Pandas
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Data Analysis in Python with Pandas

Getting an introduction to doing data analysis with the Python pandas library with hours of video and code.
Bestselling
4.5 (443 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
4,525 students enrolled
Created by Bill Chambers
Last updated 8/2015
English
English
Current price: $10 Original price: $20 Discount: 50% off
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Includes:
  • 5 hours on-demand video
  • 2 Articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Perform data analysis with python using the pandas library.
  • Understand some of the basic concepts of data analysis.
  • Have used n-dimensional arrays in NumPy as well as the pandas Series and DataFrames to analyze data.
  • Learned the basics of plotting with matplotlib
View Curriculum
Requirements
  • Students need to have Python installed on their computer.
  • Students should be familiar with basic data analysis concepts.
  • Students should have experience writing, at a minimum, basic programs in python.
Description

Ever wonder how you can best analyze data in python? Wondering how you can advance your career beyond doing basic analysis in excel? Want to take the skills you already have from the R language and learn how to do the same thing in python and pandas?

THEN THIS COURSE IS FOR YOU!

By taking the course, you will master the fundamental data analysis methods in python and pandas!

You’ll also get access to all the code for future reference, new updated videos, and future additions for FREE! You'll Learn the most popular Python Data Analysis Technologies!

By the end of this course:

- Understand the data analysis ecosystem in Python.

- Learn how to use the pandas data analysis library to analyze data sets

- Create how to create basic plots of data using MatPlotLib

- Analyze real datasets to better understand techniques for data analysis

At the end of this course you will have learned a lot of the tips and tricks that cut down my learning curve as a business analyst and as a Master’s Student at UC Berkeley doing data analysis. I designed this course for those that have an intermediate programming ability and are ready to take their data analysis skills to the next level.

You’ll understand cutting edge techniques used by data analysts, data scientists, and other data researches in Silicon Valley.

Complete with working files and code samples, over 5 hours with 40+ lectures you’ll learn all that you need to know to turn around and apply data analysis strategies to the data that you work with. You’ll be able to work along side the instructor as we work through different data sets and data analysis approaches using cutting edge data science tools!

Who is the target audience?
  • This course is best suited for people that need a deeper understanding of data analysis tools available today.
  • This course is not suited for those that want to learn how to program and have no prior programming experience.
  • This course is great for introductory to intermediate python programmers or those that come from a statistical software background like R or SPSS.
  • Analysts who want to better understand a technical approach to analyzing data.
  • Scientists who want to step away from more academic programming languages and use a general purpose language like python.
  • Programmers who are coming from a technical background but want to understand the pydata ecosystem a bit better.
  • Those that are interested in learning a bit more about data analysis.
Students Who Viewed This Course Also Viewed
Curriculum For This Course
34 Lectures
04:49:46
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Introduction to the Course
4 Lectures 04:33

This video is a general video introduction to the course.

Preview 03:18

This video gives you basic instruction on how to install what you'll need for this course.

Installation Instructions
00:49

These are the written directions for how to setup your environment.

Setting up your Environment
00:09

This is a link to all the data and files that are used in this course.

Course Resources - All Files and Data
00:16
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IPython Notebooks and Raw Python Data Analysis
5 Lectures 39:21

This video introduces you to the IPython Notebook.

Tools of the Trade, The IPython Notebook
10:06

This video introduces you to the concept of mapping and how it's done in raw python.

Maps
07:07

This video introduces you to the concept of filtering and how it's done in raw python.

Filters
05:45

This video introduces you to the concept of list comprehensions.

List Comprehensions
06:40

This video introduces you to the concept of lambda functions and how they work in python.

Lambda Functions
09:43
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The Basics of NumPy
6 Lectures 01:03:30

This video introduces you to the basic usage and concept of NumPy.

NumPy Array Basics
06:09

This video introduces you to the basic usage and concept of boolean selection in NumPy.

Boolean Selection
10:20

This video introduces you to the basic usage of some helpful methods in NumPy.

Helpful Methods and Shortcuts
12:59

This video introduces you to the basic usage and concept of vectorization in NumPy.

Vectorization
07:08

This video introduces you to the basic usage and concept of multi-dimensional arrays in NumPy.

Multi-Dimensional Arrays
14:12

This video introduces you to the basic usage and concept of querying, slicing, and combining arrays in NumPy.

Querying Slicing, Combining, and Splitting Arrays
12:42
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Pandas Basics
1 Lecture 10:40

This video gives you an overall introduction to the basic usage and concepts of pandas.

Preview 10:40
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pandas Series
5 Lectures 43:33

This video gives you an overall introduction to the basic usage and concepts of the pandas Series.

Overview of the pandas Series
07:25

This video gives you an overall introduction to look ups, selections, and indexing in pandas Series.

Look Ups, Selections, and Indexing
11:01

This video gives you shows you how to perform advanced indexing in the pandas Series.

Advanced Indexing Options
06:56

This video shows you how to handle NaN values, perform reindexing, and Filling Methods.

Handling NaN Values, Reindexing, Filling Methods and Series Addition
12:06

This video shows you how to perform Series multiplication, reindexing, and mapping.

Series Multiplication, More Reindexing, and Mapping
06:05
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pandas DataFrame
9 Lectures 01:22:51

This video gives you an overall introduction to the basic usage and concepts of the pandas DataFrame.

DataFrame Basics
10:04

This video teaches you how to read files, plot, and understand some basic methods with the DataFrame.

Reading Files, Plotting, and Basic Methods
10:45

In this video you'll learn more about plotting, performing joins, datetime indexing, and writing files.

More Plotting, Joins, Basic DateTime Indexing, and Writing to Files
11:53

In this video you'll add and reset columns and performing mapping with functions.

Adding & Reseting Columns, Mapping with Functions
07:14

In this video you learn how to do more mapping, handle some NaN values, understand more plotting and how to perform correlations.

More Mapping, Filling NaN values, Plotting, Correlations, and Histograms
10:17

In this video you learn how to do more plotting, learn about rolling calculations, and more datetime indexing.

More Plotting, Rolling Calculations, Basic DateTime Indexing
05:52

In this video you'll learn some analysis concepts, how to fill in NaN values, and get cumulative values.

Analysis Concepts, Filling NaN Values, Cumulative Sums and Value Counts
09:20

In this video you'll learn about data maintenance, and how to add remove columns.

Data Maintenance, Adding/ Removing Columns and Rows
08:18

In this video you'll learn about basic grouping concepts and some concepts of aggregate functions.

Basic Grouping, Concepts of Aggregate Functions
09:08
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BONUS: Advanced pandas Topics
4 Lectures 45:10

In this video you'll learn about pandas.io.Data, and some advanced indexing concepts.

pandas.IO.Data, Panels and Hierarchical Indexing
11:42

In this video you'll learn more about reading csv data, html data, performing binning and understand categorical data.

Advanced Reading Csvs/HTML, Binning, Categorical Data
12:43

In this video you'll learn about advanced grouping and aggregation functions.

Advanced Groupings and Aggregate Functions
07:56

In this video you'll learn about advanced grouping and apply and transform functions.

More Grouping Functions including Apply and Transform
12:49
About the Instructor
Bill Chambers
4.5 Average rating
441 Reviews
4,525 Students
1 Course
Data Scientist at UC Berkeley

Bill Chambers is currently pursuing a Master’s in Information Management and Systems at the UC Berkeley School of Information. Before pursuing this degree, he focused on data architecture and systems scaling at his last employer. He re-architected the company’s entire internal systems operations including redeploying Salesforce internally, implementing Hubspot’s marketing automation software, and integrating Totango’s customer analytics platform. Bill was also responsible for providing operational metrics through statistical analysis using Python (specifically the pandas data analysis library). After UC Berkeley, Bill hopes to help other businesses improve the way their businesses work through data.