Python Data Analysis Bootcamp: From Beginner to Pandas Pro in 1 Hour

Get data from data sources, clean, transform, merge, combine data, prepare data to your required subset of rows, columns, and structure.

Python for Data Analysis

Course summary

You would learn to manipulate large and varied datasets by getting hands-on, practical experience working on real-life data problems.

You would gain working knowledge of the most commonly used Python modules for data scientists.

Get data from data sources, merge and combine it into one or more data sets.

Clean your data, re-structure, transform, and manipulate data to make sure it is suitable for your use case.

Course delivery

• Location: Online or In Classroom
• Instructor-led: No training-bots in our classroom yet
• Joining Instructions: Full joining instructions will be sent ahead of the course.
• Certificate: PCWorkshops certificate is issued on completion
• Notes: Includes notes, exercises, code samples, some videos.

Laptops, software and datasets:

• Laptops: Bring your own device
• Data sets: We will provide sample datasets beforehand

Practical

This course is hands-on and very practical. You will be given many examples and challenges to try out on your own

Key learning outcomes

At the end of this course, you will be able to:

Easily clean, prepare, transform, and summarize data trends from large data sets

Who should come?

• Anyone who needs to manage or interact with large datasets.
• Some basic experience working with data would be useful but is not required to follow the course.
• The course does not require any prior programming experience.

Course Outline:

Session 1: Importing your data to Python, from various sources for different data structures.

Session 2: Pandas

The Python Pandas: Dataframes, Series, Indexing, Sorting, Filter, Slicing, Iteration, Functions, Date/Time Functionality. Time series.

Session 3: Data Cleaning and preparation

Random Sampling. Finding and filtering data, Replacing values, Finding and filtering Missing data, Remove Duplicates, String objects, Regex. Transforming data using function and mapping, Renaming Axis Indexes, Discretization and Binning.

Session 4: Data Wrangling

Hierarchical Indexing, Reorder, Sorting, Stastitics, Dataframe Joins, Merging, Concatenation, and Overlap. Reshaping and pivoting.

Your trainer:

Sarah Barnard has been a software and database developer for 20+ years. She founded, grew and sold 3 software training companies during this time. She has published 5000+ educational programming scripts, 49 training manuals available on Shopify, manages a Udemy channel and a Programming Languages Meetup group