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Data Analysis in Python with Pandas

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Data Analysis in Python with Pandas, available at $34.99, has an average rating of 3.95, with 34 lectures, based on 761 reviews, and has 5792 subscribers.

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You will learn about 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 This course is ideal for individuals who are This course is best suited for people that need a deeper understanding of data analysis tools available today. or This course is not suited for those that want to learn how to program and have no prior programming experience. or This course is great for introductory to intermediate python programmers or those that come from a statistical software background like R or SPSS. or Analysts who want to better understand a technical approach to analyzing data. or Scientists who want to step away from more academic programming languages and use a general purpose language like python. or Programmers who are coming from a technical background but want to understand the pydata ecosystem a bit better. or Those that are interested in learning a bit more about data analysis. It is particularly useful for This course is best suited for people that need a deeper understanding of data analysis tools available today. or This course is not suited for those that want to learn how to program and have no prior programming experience. or This course is great for introductory to intermediate python programmers or those that come from a statistical software background like R or SPSS. or Analysts who want to better understand a technical approach to analyzing data. or Scientists who want to step away from more academic programming languages and use a general purpose language like python. or Programmers who are coming from a technical background but want to understand the pydata ecosystem a bit better. or Those that are interested in learning a bit more about data analysis.

Enroll now: Data Analysis in Python with Pandas

Summary

Title: Data Analysis in Python with Pandas

Price: $34.99

Average Rating: 3.95

Number of Lectures: 34

Number of Published Lectures: 34

Number of Curriculum Items: 34

Number of Published Curriculum Objects: 34

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

  • 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.

Target Audiences

  • 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.

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!

Course Curriculum

Chapter 1: Introduction to the Course

Lecture 1: What is this Course?

Lecture 2: Installation Instructions

Lecture 3: Setting up your Environment

Lecture 4: Course Resources – All Files and Data

Chapter 2: IPython Notebooks and Raw Python Data Analysis

Lecture 1: Tools of the Trade, The IPython Notebook

Lecture 2: Maps

Lecture 3: Filters

Lecture 4: List Comprehensions

Lecture 5: Lambda Functions

Chapter 3: The Basics of NumPy

Lecture 1: NumPy Array Basics

Lecture 2: Boolean Selection

Lecture 3: Helpful Methods and Shortcuts

Lecture 4: Vectorization

Lecture 5: Multi-Dimensional Arrays

Lecture 6: Querying Slicing, Combining, and Splitting Arrays

Chapter 4: Pandas Basics

Lecture 1: General pandas Concepts

Chapter 5: pandas Series

Lecture 1: Overview of the pandas Series

Lecture 2: Look Ups, Selections, and Indexing

Lecture 3: Advanced Indexing Options

Lecture 4: Handling NaN Values, Reindexing, Filling Methods and Series Addition

Lecture 5: Series Multiplication, More Reindexing, and Mapping

Chapter 6: pandas DataFrame

Lecture 1: DataFrame Basics

Lecture 2: Reading Files, Plotting, and Basic Methods

Lecture 3: More Plotting, Joins, Basic DateTime Indexing, and Writing to Files

Lecture 4: Adding & Reseting Columns, Mapping with Functions

Lecture 5: More Mapping, Filling NaN values, Plotting, Correlations, and Histograms

Lecture 6: More Plotting, Rolling Calculations, Basic DateTime Indexing

Lecture 7: Analysis Concepts, Filling NaN Values, Cumulative Sums and Value Counts

Lecture 8: Data Maintenance, Adding/ Removing Columns and Rows

Lecture 9: Basic Grouping, Concepts of Aggregate Functions

Chapter 7: BONUS: Advanced pandas Topics

Lecture 1: pandas.IO.Data, Panels and Hierarchical Indexing

Lecture 2: Advanced Reading Csvs/HTML, Binning, Categorical Data

Lecture 3: Advanced Groupings and Aggregate Functions

Lecture 4: More Grouping Functions including Apply and Transform

Instructors

Rating Distribution

  • 1 stars: 7 votes
  • 2 stars: 16 votes
  • 3 stars: 108 votes
  • 4 stars: 298 votes
  • 5 stars: 332 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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