Cleaning Data in R
RStudio
| Intermediate
- 13 videos | 1h 2m 7s
- Includes Assessment
- Earns a Badge
R is a programming language that is essential for data science, used for statistical computing and graphics. In this 13-video course, learners explore essential methods for wrangling and cleaning data with R. Begin by recognizing types of unclean data and criteria for ensuring data quality. First, learners see how to fetch a JSON (JavaScript Object Notation) document over HTTP and load data into a dplyr table. Learn how to load multiple sheets from an Excel document and how to handle common errors encountered when reading CSV (comma-separated values) data. Read data from a relational database with a SQL (structured query language) query. Explore joining tabular data by combining two related data sets by using a join operation, and spreading data-reshaping tabular data by spreading values from rows to columns. Look at summarizing data, applying a summary function using dplyr; imputing data, using mean imputation to replace missing values; and extracting matches, using a regular expression and data wrangling tools from the tidyverse package. The closing exercise practices data wrangling functions using R.
WHAT YOU WILL LEARN
-
Recognize types of unclean data
Recognize criteria for ensuring data quality
Fetch a json document over http and load it using dplyr
Load multiple sheets from an excel document
Handle common errors encountered when reading csv data
Read data from a relational database using a sql query -
Combine two related datasets using a join operation
Reshape tabular data by spreading values from rows to columns
Apply a summary function using dplyr
Use mean imputation to replace missing values
Use a regular expression to extract data into a new column
Practice applying data wrangling functions using r
IN THIS COURSE
-
1m 13s
-
4m 22sUpon completion of this video, you will be able to recognize types of data that are not clean. FREE ACCESS
-
3. Data Quality3m 44sAfter completing this video, you will be able to recognize criteria for ensuring data quality. FREE ACCESS
-
4. Downloading JSON Data8m 11sIn this video, learn how to fetch a JSON document over HTTP and load it using dplyr. FREE ACCESS
-
5. Excel Sheets4m 8sDuring this video, you will learn how to load multiple sheets from an Excel document. FREE ACCESS
-
6. Reading Dirty CSVs8m 40sFind out how to handle common errors encountered when reading data from a CSV file. FREE ACCESS
-
7. Querying Relational Databases5m 13sFind out how to read data from a relational database using SQL queries. FREE ACCESS
-
8. Joining Tabular Data2m 59sIn this video, find out how to combine two related datasets using a join operation. FREE ACCESS
-
9. Spreading Data3m 38sIn this video, you will reshape tabular data by spreading values from columns to rows. FREE ACCESS
-
10. Summarizing Data4m 23sDuring this video, you will learn how to apply a summary function using dplyr. FREE ACCESS
-
11. Imputing Data5m 40sTo replace missing values, find out how to use mean imputation. FREE ACCESS
-
12. Extracting Matches4m 42sIn this video, you will learn how to use a regular expression to extract data into a new column. FREE ACCESS
-
13. Exercise: Wrangling Data5m 14sDuring this video, you will learn how to apply data wrangling functions using R. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.
