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File	Size
!! IMPORTANT Note !!.txt	287.00 B
!!! Please Support !!! [CoursesGhar.Com].txt	197.00 B
00. Websites You May Like/CoursesGhar.Com.url	114.00 B
00. Websites You May Like/New Internet Shortcut.url	114.00 B
telegram @coursesghargate.url	128.00 B
Uploaded by [Coursesghar.com].txt	1.10 kB
Visit coursesghar.com for more awesome tutorials.url	114.00 B
[1] Introduction/[1] Make your data make sense.mp4	12.89 MB
[1] Introduction/[1] Make your data make sense.srt	2.49 kB
[1] Introduction/[2] Using the exercise files.mp4	1.52 MB
[1] Introduction/[2] Using the exercise files.srt	1.64 kB
[2] 1. What Is R/[1] R in context.mp4	16.70 MB
[2] 1. What Is R/[1] R in context.srt	10.91 kB
[2] 1. What Is R/[2] Data science with R A case study.mp4	32.57 MB
[2] 1. What Is R/[2] Data science with R A case study.srt	22.49 kB
[3] 2. Getting Started/[10] Piping commands with %%.mp4	7.58 MB
[3] 2. Getting Started/[10] Piping commands with %%.srt	8.11 kB
[3] 2. Getting Started/[1] Installing R.mp4	4.21 MB
[3] 2. Getting Started/[1] Installing R.srt	2.58 kB
[3] 2. Getting Started/[2] Environments for R.mp4	8.97 MB
[3] 2. Getting Started/[2] Environments for R.srt	5.85 kB
[3] 2. Getting Started/[3] Installing RStudio.mp4	3.97 MB
[3] 2. Getting Started/[3] Installing RStudio.srt	2.16 kB
[3] 2. Getting Started/[4] Navigating the RStudio environment.mp4	16.57 MB
[3] 2. Getting Started/[4] Navigating the RStudio environment.srt	10.36 kB
[3] 2. Getting Started/[5] Entering data.mp4	16.71 MB
[3] 2. Getting Started/[5] Entering data.srt	12.72 kB
[3] 2. Getting Started/[6] Data types and structures.mp4	28.45 MB
[3] 2. Getting Started/[6] Data types and structures.srt	21.95 kB
[3] 2. Getting Started/[7] Comments and headers.mp4	12.23 MB
[3] 2. Getting Started/[7] Comments and headers.srt	8.45 kB
[3] 2. Getting Started/[8] Packages for R.mp4	16.45 MB
[3] 2. Getting Started/[8] Packages for R.srt	8.08 kB
[3] 2. Getting Started/[9] The tidyverse.mp4	9.53 MB
[3] 2. Getting Started/[9] The tidyverse.srt	4.62 kB
[4] 3. Importing Data/[1] R's built-in datasets.mp4	15.08 MB
[4] 3. Importing Data/[1] R's built-in datasets.srt	9.04 kB
[4] 3. Importing Data/[2] Exploring sample datasets with pacman.mp4	19.08 MB
[4] 3. Importing Data/[2] Exploring sample datasets with pacman.srt	11.52 kB
[4] 3. Importing Data/[3] Importing data from a spreadsheet.mp4	15.68 MB
[4] 3. Importing Data/[3] Importing data from a spreadsheet.srt	9.90 kB
[4] 3. Importing Data/[4] Importing XML data.mp4	17.77 MB
[4] 3. Importing Data/[4] Importing XML data.srt	9.89 kB
[4] 3. Importing Data/[5] Importing JSON data.mp4	18.88 MB
[4] 3. Importing Data/[5] Importing JSON data.srt	10.37 kB
[4] 3. Importing Data/[6] Saving data in native R formats.mp4	18.46 MB
[4] 3. Importing Data/[6] Saving data in native R formats.srt	11.82 kB
[5] 4. Visualizing Data with ggplot2/[1] Introduction to ggplot2.mp4	13.44 MB
[5] 4. Visualizing Data with ggplot2/[1] Introduction to ggplot2.srt	7.58 kB
[5] 4. Visualizing Data with ggplot2/[2] Using colors in R.mp4	15.07 MB
[5] 4. Visualizing Data with ggplot2/[2] Using colors in R.srt	8.92 kB
[5] 4. Visualizing Data with ggplot2/[3] Using color palettes.mp4	27.20 MB
[5] 4. Visualizing Data with ggplot2/[3] Using color palettes.srt	14.64 kB
[5] 4. Visualizing Data with ggplot2/[4] Creating bar charts.mp4	24.05 MB
[5] 4. Visualizing Data with ggplot2/[4] Creating bar charts.srt	17.01 kB
[5] 4. Visualizing Data with ggplot2/[5] Creating histograms.mp4	14.92 MB
[5] 4. Visualizing Data with ggplot2/[5] Creating histograms.srt	9.66 kB
[5] 4. Visualizing Data with ggplot2/[6] Creating box plots.mp4	13.59 MB
[5] 4. Visualizing Data with ggplot2/[6] Creating box plots.srt	10.73 kB
[5] 4. Visualizing Data with ggplot2/[7] Creating scatterplots.mp4	15.85 MB
[5] 4. Visualizing Data with ggplot2/[7] Creating scatterplots.srt	10.68 kB
[5] 4. Visualizing Data with ggplot2/[8] Creating multiple graphs.mp4	11.34 MB
[5] 4. Visualizing Data with ggplot2/[8] Creating multiple graphs.srt	7.52 kB
[5] 4. Visualizing Data with ggplot2/[9] Creating cluster charts.mp4	22.64 MB
[5] 4. Visualizing Data with ggplot2/[9] Creating cluster charts.srt	15.53 kB
[6] 5. Wrangling Data/[10] Filtering cases and subgroups.mp4	20.88 MB
[6] 5. Wrangling Data/[10] Filtering cases and subgroups.srt	13.65 kB
[6] 5. Wrangling Data/[1] Creating tidy data.mp4	27.48 MB
[6] 5. Wrangling Data/[1] Creating tidy data.srt	17.92 kB
[6] 5. Wrangling Data/[2] Using tibbles.mp4	12.75 MB
[6] 5. Wrangling Data/[2] Using tibbles.srt	9.28 kB
[6] 5. Wrangling Data/[3] Using data.table.mp4	14.03 MB
[6] 5. Wrangling Data/[3] Using data.table.srt	8.89 kB
[6] 5. Wrangling Data/[4] Converting data from wide to tall and from tall to wide.mp4	10.90 MB
[6] 5. Wrangling Data/[4] Converting data from wide to tall and from tall to wide.srt	7.59 kB
[6] 5. Wrangling Data/[5] Converting data from tables to rows.mp4	13.91 MB
[6] 5. Wrangling Data/[5] Converting data from tables to rows.srt	8.52 kB
[6] 5. Wrangling Data/[6] Working with dates and times.mp4	17.76 MB
[6] 5. Wrangling Data/[6] Working with dates and times.srt	11.03 kB
[6] 5. Wrangling Data/[7] Working with list data.mp4	14.06 MB
[6] 5. Wrangling Data/[7] Working with list data.srt	9.51 kB
[6] 5. Wrangling Data/[8] Working with XML data.mp4	15.21 MB
[6] 5. Wrangling Data/[8] Working with XML data.srt	9.20 kB
[6] 5. Wrangling Data/[9] Working with categorical variables.mp4	15.96 MB
[6] 5. Wrangling Data/[9] Working with categorical variables.srt	13.00 kB
[7] 6. Recoding Data/[1] Recoding categorical data.mp4	25.14 MB
[7] 6. Recoding Data/[1] Recoding categorical data.srt	17.14 kB
[7] 6. Recoding Data/[2] Recoding quantitative data.mp4	19.54 MB
[7] 6. Recoding Data/[2] Recoding quantitative data.srt	12.54 kB
[7] 6. Recoding Data/[3] Transforming outliers.mp4	21.68 MB
[7] 6. Recoding Data/[3] Transforming outliers.srt	16.13 kB
[7] 6. Recoding Data/[4] Creating scale scores by counting.mp4	14.43 MB
[7] 6. Recoding Data/[4] Creating scale scores by counting.srt	9.97 kB
[7] 6. Recoding Data/[5] Creating scale scores by averaging.mp4	8.74 MB
[7] 6. Recoding Data/[5] Creating scale scores by averaging.srt	6.05 kB
[8] Conclusion/[1] Next steps.mp4	6.24 MB
[8] Conclusion/[1] Next steps.srt	3.85 kB

Description

LinkedIn Learning - R Essential Training Wrangling and Visualizing Data [CoursesGhar]

Trying to locate meaning and direction in big data is difficult. R can help you find your way. R is a statistical programming language to analyze and visualize the relationships between large amounts of data. This training series provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks. In part one, instructor Barton Poulson shows how to get R and popular R packages up and running and start importing, cleaning, and converting data for analysis. He also shows how to create visualizations such as bar charts, histograms, and scatterplots and transform categorical, qualitative, and outlier data to best meet your research questions and the requirements of your algorithms.
Learning objectives
Installing R
Entering data
Packages for R
Importing XLS, XML, and JSON data
Visualizing data with ggplot2
Creating charts, histograms, scatterplots, and graphs
Converting data
Filtering cases and subgroups
Recoding data
Creating scale scores