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This course is ideal for anyone who knows basic R concepts and would like to prepare for real-world data analysis with R.

Have you ever had a problem with importing data into R? Was every file in a different format? Did you have trouble picking the right packages for your needs? And then, after all that headache, you run into errors or missing data. Perhaps you've also struggled with strings or dates in data sets.

Working with real-world datasets can be tough. It's certainly different than working with data sets from courses, which have usually been cleaned ahead of time and sometimes contain fictitious data. In this course, you'll learn how to handle problems with data so you're prepared for real-world data analysis with R.

We'll focus on reading and writing into files in different formats, such as CSV, Excel, and others. The course will teach you the best solutions and practices for the task at hand, including which packages you should use.

After we import our data into R, we'll learn how to prepare it for analysis. We'll learn how to clean data, change the structure of data (from wide to long format, using the spread() and gather() functions), remove redundant information (using filter()), and handle duplicates (using duplicated()).

Additionally, we'll take a look at special data types like strings and dates that tend to cause problems in data analysis. For example, have you ever tried converting a string into a date or removing duplicate characters from a string? If so, then you probably know that it can be tricky. After you take this course, you should have a good grasp on how to work with these data types.

Toward the end of the course, we'll focus on findings errors and accounting for missing values. Finally, you will get the opportunity to review everything you learned with a cumulative quiz.

What's in It for Me?

  • 99 interactive exercises. Learn at your own pace, from anywhere and anytime. Interact with hands-on exercises for improved retention.
  • Lifetime access to the course. When you purchase the course, you'll get instant personal access to all of its content.
  • Certificate of completion. After you successfully finish all of the exercises, you'll get a downloadable PDF certificate to showcase your accomplishment.
  • 30-day money back guarantee. If you're not satisfied with the quality of the course, you can get a refund within 30 days of your purchase.
  • Hints for the exercises. You can ask questions and share insights with other members of the Vertabelo Academy community through the Disqus tab. You can also drop us a line at academy@vertabelo.com–we'll be more than happy to answer! 😉

Requirements

This Course Will Teach You How To:

  • Import data from files – how to handle different formats in R.
  • Prepare your data for further analysis (data cleaning basics).
  • Work with strings and dates (lubridate).
  • Handle errors and missing data in files.

Who Should Take This Course?

  • Students taking classes on data analysis.
  • Data and business analysts.
  • Beginner data scientists.
  • Anyone who works with different data.
  • Anyone interested in data science or statistical analysis.
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    One to Rule 'Em All

    Includes 40 courses Python Basics. Part 1, Python Basics. Part 2, Python Basics. Part 3, Python Data Structures in Practice, Built-in Algorithms in Python, Working with Strings in Python, SQL Basics, SQL Practice Set, SQL JOINs, Standard SQL Functions, Creating Basic SQL Reports, Window Functions, Revenue Trend Analysis in SQL, How to INSERT, UPDATE, and DELETE Data in SQL, Recursive Queries, Creating Tables in SQL, Introduction to R, Tidyverse, Data Visualization 101, Statistics 101, SQL Basics in MS SQL Server, How to Insert, Update, or Delete Data in MS SQL Server, Common Functions in MS SQL Server, Revenue Trend Analysis in SQL Server, Creating Basic SQL Reports in SQL Server, Window Functions in MS SQL Server, Recursive Queries in MS SQL Server, GROUP BY Extensions in MS SQL Server, How to Read and Write CSV Files in Python, Introduction to Python for Data Science, How to Read and Write JSON Files in Python, Lists and Functions in R, Data Manipulation in R, SQL Basics in PostgreSQL, PostgreSQL JOINs, SQL Practice Set in PostgreSQL, Window Functions in PostgreSQL, Recursive Queries in PostgreSQL, Writing User-Defined Functions in PostgreSQL, PostGIS

    Bundle price $199

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    Table of contents

    Progress: 0% completed 0 of 99 exercises done

    1. Importing Data

    Learn how to import different types of data: from CSV to Excel files.

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    0% completed 0 of 16 exercises done

    2. Data Cleaning

    Find out how to get rid of unwanted values in your data.

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    3. Working with Strings

    Learn about strings – how to manipulate them with ease.

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    4. Working with Dates

    Learn how to work with date and time data.

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    5. Handling Missing Values and Errors

    Find out how to handle missing values and data errors in R.

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    6. Final Quiz

    Test your understanding of everything you've learned in the course.

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