https://github.com/trainingbypackt/data-wrangling-with-python-elearning

Creating actionable data from raw sources
https://github.com/trainingbypackt/data-wrangling-with-python-elearning

beautifulsoup4 data-science data-wrangling matplotlib numpy pandas python web-scraping

Last synced: about 1 month ago
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Creating actionable data from raw sources

• Host: GitHub
• URL: https://github.com/trainingbypackt/data-wrangling-with-python-elearning
• Owner: TrainingByPackt
• License: mit
• Created: 2019-04-27T08:07:26.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-04-27T08:20:12.000Z (over 5 years ago)
• Last Synced: 2023-03-02T20:56:42.719Z (almost 2 years ago)
• Topics: beautifulsoup4, data-science, data-wrangling, matplotlib, numpy, pandas, python, web-scraping
• Language: Jupyter Notebook
• Size: 8.24 MB
• Stars: 2
• Watchers: 4
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Data Wrangling with Python [eLearning]

Data is the new oil, but it comes crude. To do anything meaningful - modeling, visualization, machine learning, for predictive analysis – you first need to wrestle and wrangle with data. Data Wrangling with Python teaches you the essentials that will get you up and running with data wrangling in no time.

## What you will learn

* Use and manipulate complex and simple data structures

* Harness the full potential of DataFrames and numpy.array at run time

* Perform web scraping with BeautifulSoup4 and html5lib

* Execute advanced string search and manipulation with RegEX

* Handle outliers and perform data imputation with Pandas

* Use descriptive statistics and plotting techniques

* Practice data wrangling and modeling using data generation techniques

### Hardware requirements

For an optimal learning experience, we recommend the following hardware configuration:

* Processor: Intel Core i5 or equivalent

* Memory: 4GB RAM (8 GB Preferred)

* Storage: 35 GB available space

### Software requirements

You must also install in advance the following software:

* OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu Linux, or the latest version of OS X

* Browser: Google Chrome/Mozilla Firefox Latest Version

* Notepad++/Sublime Text as IDE (Optional, as you can practice everything using Jupyter notecourse on your browser)

* Python 3.4+ (latest is Python 3.7) installed (from https://python.org)

* Python libraries as needed (Jupyter, Numpy, Pandas, Matplotlib, BeautifulSoup4, and so)