Python Pandas and Jupyter ETL and Data wrangling

TRAINING COURSE

Details

Python is an incredibly popular and powerful language for programming all sorts of functions and its use in data science has grown significantly over the years. There are tools such as Jupyter Notebooks which allow users to share live code, documentation, graphs, plots, and visualizations in a notebook, and Pandas, a software library used for data manipulation and analysis. With these tools you'll be able to easily create an ETL (extract, transform, load) pipeline and wrangle your data into clean, easily-accessible formats.

In this course you will learn how to:

  • Create and use Jupyter Notebooks
  • Create Pandas Dataframes and perform operations
  • Importing and Export different data types
  • Transform, reformat and organise data

Delivery Methods

Delivery Method Duration
Classroom
2 Days Get a Quote
Live Virtual Training
2 Days Get a Quote

Discounts Available

Save up to 10% by booking and paying 10 business days before the course.

Brochure:

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Information may change without notice.

Audience

  • Data scientists
  • Programmers
  • Business analysts 
  • Engineers
  • Scientists

 

Pre-Requisites

Leading Training's Python Course or equivalent knowledge

Course Outline / Curriculum

Using Jupyter Notebooks

  • Starting/Opening Notebook
  • Using VS Code
  • Navigating and Editing
  • Short cut keys
  • Productivity hints and tips in iPython
  • Pandas Dataframes

Creating Dataframes

  • Selecting Data
  • Setting data and indices
  • Basic Operations

Importing/Exporting Data

  • SQL
  • CSV and Excel
  • HDF5

Data Wrangling

  • Merge Concat
  • break it into pieces
  • Join
  • Append
  • Grouping
  • Reshaping
  • Pivot Tables
  • Time Series
  • Time zone representation
  • Converting to another time zone
  • Converting between time span representations
  • Categoricals

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