Crash Course: Data Analytics in Python using Pandas

Simpliv

Course

Online

£ 150 VAT inc.

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Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

The demand for data engineers is greater than ever. So, there is no better time to upskill; learn Python and specifically data engineering.I'll take you through the core concepts of dataframes, which are a key data structure within Pandas. We'll learn to ingest, clean and analyse the data and by the end of the course, you'll be in a position to use Python & Pandas on your own data to extract valuable insight.The idea isn’t to become an expert through this course. The idea is to become confident in the core concepts of Python and Pandas so you can solve real-world problems today and so you can continue your learning by doing.Because, nobody becomes an expert through taking a course (no matter how long they are), you only truly become an expert by getting out there & solving problems.For this course, you'll need some basic Python knowledge, which you can gain from my No Nonsense Python course here on Simpliv.You will need to have Python installed and the Pandas library installed - which you can do using 'pip install pandas'.Who this course is for:Beginner Python Developers
Those interested in data analytics

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Perform data analysis with the Pandas library
Learn about dataframes and how to conduct data analysis in Python
Understand how to handle missing values in your data
Understand how to handle & clean up messy data

Beginner Python Developers
Those interested in data analytics

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Reviews

This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Project
  • Cleaning

Course programme

Introduction 1 lecture 00:29 Introduction Introduction 1 lecture 00:29 Introduction Introduction Introduction Introduction Introduction A Project to Get us Started 4 lectures 19:34 Project introduction: What's the data & what do we want to achieve? Ingesting data & cleaning it up Initial insight from the data Extracting a little more insight A Project to Get us Started 4 lectures 19:34 Project introduction: What's the data & what do we want to achieve? Ingesting data & cleaning it up Initial insight from the data Extracting a little more insight Project introduction: What's the data & what do we want to achieve? Project introduction: What's the data & what do we want to achieve? Project introduction: What's the data & what do we want to achieve? Project introduction: What's the data & what do we want to achieve? Ingesting data & cleaning it up Ingesting data & cleaning it up Ingesting data & cleaning it up Ingesting data & cleaning it up Initial insight from the data Initial insight from the data Initial insight from the data Initial insight from the data Extracting a little more insight Extracting a little more insight Extracting a little more insight Extracting a little more insight The Pandas Essentials 11 lectures 29:28 Importing data Inspecting our dataframe - what do we have to work with? Handling missing values Removing duplicated data Where Statements Selecting specific fields from the dataframe Replacing values in our dataframe Group By Ranking our dataframes on a specific field value The Apply function: data cleanup & additional insight Write dataframes back to files The Pandas Essentials 11 lectures 29:28 Importing data Inspecting our dataframe - what do we have to work with? Handling missing values Removing duplicated data Where Statements Selecting specific fields from the dataframe Replacing values in our dataframe Group By Ranking our dataframes on a specific field value The Apply function: data cleanup & additional insight Write dataframes back to files Importing data Importing data Importing data Importing data Inspecting our dataframe - what do we have to work with? Inspecting our dataframe - what do we have to work with? Inspecting our dataframe - what do we have to work with? Inspecting our dataframe - what do we have to work with? Handling missing values Handling missing values Handling missing values Handling missing values Removing duplicated data Removing duplicated data Removing duplicated data Removing duplicated data Where Statements Where Statements Where Statements Where Statements Selecting specific fields from the dataframe Selecting specific fields from the dataframe Selecting specific fields from the dataframe Selecting specific fields from the dataframe Replacing values in our dataframe Replacing values in our dataframe Replacing values in our dataframe Replacing values in our dataframe Group By Group By Group By Group By Ranking our dataframes on a specific field value Ranking our dataframes on a specific field value Ranking our dataframes on a specific field value Ranking our dataframes on a specific field value The Apply function: data cleanup & additional insight The Apply function: data cleanup & additional insight The Apply function: data cleanup & additional insight The Apply function: data cleanup & additional insight Write dataframes back to files Write dataframes back to files Write dataframes back to files Write dataframes back to files Practicing What we have Learned 2 lectures 06:52 Your challenge, if you accept it Challenge solution Practicing What we have Learned 2 lectures 06:52 Your challenge, if you accept it Challenge solution Your challenge, if you accept it Your challenge, if you accept it Your challenge, if you accept it Your challenge, if you accept it Challenge solution Challenge solution Challenge solution Challenge solution Conclusion 2 lectures 02:56 A real world example of using Pandas Thank you Conclusion 2 lectures 02:56 A real world example of using Pandas Thank you A real world example of using Pandas A real world example of using Pandas A real world example of using Pandas A real world example of using Pandas Thank you Thank you Thank you Thank you

Additional information

Basic Python - from my FREE No Nonsense Python Course The Pandas library should be installed - which you can do using 'pip install python' Python should already be installed

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Crash Course: Data Analytics in Python using Pandas

£ 150 VAT inc.

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