Development

Data Manipulation and Analysis .

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  • 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 and . 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 is the target audience?

  • 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 Analyts operating in business who are looking to transition into Data Science by learning how to produce informative data-sets and graphs.

Created by Tony Staunton
Last updated 11/2018
English

Size: 815.64 MB

DOWNLOAD COURSE

https://www.udemy.com/python-pandas-data-manipulation-and-analysis/.



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