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Pandas For Data Analysis Training - United Kingdom

Key points about this course


Duration: 2 Days*

Support: 24/7

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  • Learn how to install pandas and run test suites.
  • Get an understanding of how to work with text data, missing data, and categorical data.
  • Learn how to store pandas DataFrame objects in Apache Parquet format.

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Course Information

Pandas for Data Analysis Training Course Overview

Pandas is an open-source python library that provides high-performance, data analysis and data structures tool for the Python programming language. Python with pandas can be used in numerous fields, such as statistics, economics, and analytics. This course is designed to provide knowledge of how to quickly and easily analyse data with Python’s powerful library- pandas.

In this 2-day course, delegates will gain comprehensive knowledge of pandas and data structures. Delegates will learn how to work with text data, missing data, and categorical data. In addition, they will get an understanding of merge, join, concatenate, reshaping and pivot tables.

During this course, delegates will become familiarised with visualisation, IDE, data validation, and extension data types. Delegates will learn how to store pandas DataFrame objects in Apache Parquet format. On completion of this course, delegates will get an understanding of various themes in pandas.

Pandas for Data Analysis Training Course Outline

The pandas: A Python Data Analysis Toolkit is a two-day course. The following is a brief synopsis of the topics that will be covered in this course.

Introduction and Installation

  • Define pandas
  • Installing pandas
  • Running Test Suite
  • Dependencies

Getting Started with pandas

  • Package Overview
  • Exploring panda
  • Essential Basic Functionality
  • Introduction to Data Structures
  • Comparison with Other Tools

User Guide

  • IO Tools
  • Indexing and Selecting Data
  • MultiIndex/Advanced Indexing
  • Merge, Join, and Concatenate
  • Reshaping and Pivot Tables
  • Working with Text Data, Missing Data, and Categorical Data
  • Nullable Integer Data Type
  • Visualisations
  • Computational Tools
  • Group By: Split-Apply-Combine
  • Time Series and Time Deltas
  • Stylings
  • Options and Settings
  • Enhancing Performance
  • Sparse Data Structures

pandas Ecosystem

  • Statistics and Machine Learning
  • Visualisation
  • IDE
  • Data Validation
  • Extension Data Types

Development Phase

  • Contributing to pandas
  • Internals
  • Extending pandas
  • Storing pandas DataFrame Objects in Apache Parquet Format
  • Themes in pandas Development

Prerequisites

There are no prerequisites to attend this course. However, a basic knowledge of programming would be beneficial.

Audience

Anyone wishes to develop their knowledge and skillset on python libraries can attend this course. This course is beneficial for those who want to make a career in data science and data analytics.

Please arrive at the venue at 8:45am.
There are no prerequisites to attend this course. However, a basic knowledge of programming would be beneficial.
Anyone wishes to develop their knowledge and skillset on python libraries can attend this course. This course is beneficial for those who want to make a career in data science and data analytics.
We are able to provide support via phone & email prior to attending, during and after the course.
Delegate pack consisting of course notes and exercises, Manual, Experienced Instructor, and Refreshments
This course is 2 days.
Once your booking has been placed and confirmed, you will receive an email which contains your course location, course overview, pre-course reading material (if required), course agenda and payment receipts
The price for Pandas for Data Analysis Training certification in the United Kingdom starts from £
The Knowledge Academy is the Leading global training provider in the world for Pandas for Data Analysis Training.
  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Key points about this course


Duration: 2 Days*

Support: 24/7

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Key points about this course


Duration: 2 Days*

Support: 24/7


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