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30-Day Money-Back Guarantee

This course includes:

  • 2.5 hours on-demand video
  • 2 articles
  • 13 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science

Learn Data Analysis with Python Pandas

Real world examples of Python Pandas to analyse large data files. Create visual representations of your data.
Rating: 3.9 out of 53.9 (56 ratings)
5,291 students
Created by Tony Staunton
Last updated 11/2018
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • How-to install Python and Anaconda - the worlds largest Data Science platform.
  • How-to create a virtual environment using Conda.
  • How-to setup the Atom Text Editor.
  • How to clone a GitHub Repository in Atom Text Editor.
  • How-to create a new branch in Atom Text Editor.
  • Use Python Pandas to read in large data-sets such as stock price information, customer information, purchase information and more.
  • Use Pandas DataFrames to work with tabular data.
  • Inspect datasets to gain quick valuable insights.
  • Use conditional filtering to select relevant information from datasets.
  • Using NumPy and Pandas together.
  • Create Pandas DataFrames from scratch.
  • Create DataFrames from Python dictionaries.
  • Using Broadcasting with DataFrames.
  • Correctly labeling data and columns.
  • Data cleansing techniques.
  • Using Python Pandas to create graphical plots such as bar, line, area, scatter etc.
  • How-to analysis datasets using statistical methods such as min, mas, mean, std.
  • Create filters in your code to extract targeted data from large datasets.
  • How-to manage time data in Python with Pandas.
  • Correctly index time data and create DateTime indexes.
  • Partial String Indexing and slicing.
  • Resampling Pandas Time Data.
  • Method Chaining.
  • Separating and Resampling.

Course content

6 sections • 32 lectures • 2h 21m total length

  • Preview03:36
  • How to access course source code
    00:25

  • Preview07:02
  • Preview04:28
  • Preview03:28
  • Preview05:44

  • Introduction to Pandas
    01:05
  • Introduction to DataFrames
    02:13
  • Inspecting Data
    17:46
  • Conditional Filtering
    03:51
  • Using NumPy and Pandas Together
    02:21
  • Creating DataFrames from NumPy
    03:03
  • Creating DataFrames from Dictionaries
    06:16
  • Using Broadcasting in Pandas
    01:40
  • Labeling data in a DataFrame
    01:29
  • Building DataFrames with Broadcasting
    01:55
  • Cleansing, Importing and Exporting Data
    12:19
  • Creating Plots with Pandas
    10:29

  • Creating Graphs with Pandas Plot Lines
    04:15
  • Creating Graphs with Pandas Scatter Plots
    04:22
  • Creating Graphs with Pandas Bar Plots
    02:01
  • Statistical Exploratory Data Analysis
    06:07
  • Filtering Data
    05:38

  • Introduction to Pandas DateTime
    00:47
  • Indexing Pandas Time Series
    05:38
  • Creating and using a DateTimeIndex
    02:08
  • Resampling Pandas Time Data
    05:36
  • Method Chaining
    02:36
  • Separating and Resampling
    02:29
  • Additional Filtering Methods
    03:05
  • Visualizing Pandas Time Data
    05:02

  • APPENDIX A: How to use the Atom Text Editor to push code to GitHub
    02:16

Requirements

  • You will need a desktop computer or laptop with Internet connection.
  • Some prior coding experience with Python would be beneficial or maybe a Python introduction course.
  • This course will walk you through installing all the necessary software and tools. Included is, how-to setup Python and Anaconda, how-to setup Atom Text Editor, how-to setup a virtual environment, how-to use GitHub and clone a repository.

Description

Python Pandas are one of the most used libraries in Python when it comes to data analysis and manipulation. Whether in finance, scientific fields, or data science, a familiarity with Pandas is a must have. This course teaches you how to work with real-world data sets for analyzing data in Python using Pandas. Not only will you learn how to manipulate and analyse data you will also learn powerful and easy to use visualization techniques for representing your data. 

This course kicks off by showing you how to get up and running using GitHub, an essential skill in your coding career. Ideally, to get the best from this course you should have some Python programming experience.

Every piece of code and dataset used in this course is available to download for free from GitHub.

Without doubt this course will teach you the necessary skills to apply basic data science techniques which are use the world over by experienced data scientists and those who spend their working day in spreadsheets.

Who this course is for:

  • Software Developers who have basic Python experience/knowledge and are looking to up-skill into the high demand area of Data Science.
  • Software Developers who work with spreadsheets and data-sets and would like to learn how to produce valuable insights from them.
  • Data Analysts operating in business who are looking to transition into Data Science by learning how to produce informative data-sets and graphs.

Instructor

Tony Staunton
Reading, writing & teaching. Over 20,000 students.
Tony Staunton
  • 4.0 Instructor Rating
  • 1,062 Reviews
  • 33,046 Students
  • 10 Courses

Hi! I'm Tony. I love to read, write and teach and you could definitely call me a bit of geek. I love all things to do with programming, productivity, books and the internet.

Previously I have run my own software business and won several awards from, most innovative startup to best product. After finding out the hard way just how stressful growing a startup into a business can be I have researched all things to do with productivity and I love helping other become more productive and avoid the mistakes I have made.

I'm passionate about teaching and I love to hear back from my students with any questions or ideas on how to improve my courses or create new ones.

My courses teach you how to programme and become more productive and you will not believe the freedom that these skills can bring. Sign up and find out for yourself why so many people are taking and recommending my courses. I genuinely believe that I have something to offer you and if you don't agree, I'll happily refund your money. 

Sign up to my courses and join me in this amazing adventure today.

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