[ FreeCourseWeb.com ] Cleaning Data In R with Tidyverse and Data.table
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h264, yuv420p, 1280x720 |ENGLISH, 44100 Hz, 2 Channels | 4h 04mn | 1.66 GB
Get your data ready for analysis with R packages tidyverse, dplyr, data.table, tidyr and more
What you'll learn
Convert raw and dirty data into clean data
Understand how clean data looks and how to achieve it
Use the R Tidyverse packages to clean data
Handle missing values in R
Detect outliers
Filter and query tables
Select a proper class for your data
Clean various classes of data (numeric, string, categorical, integer, ...)
Requirements
Use Winrar to Extract. And use a shorter path when extracting, such as C: drive
ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)
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