How to Modify and Customize Plots in R: How to Modify, Enhance and Customize Plots Created in R (RStudio) to Change from the Default Values; Here is the Free Practice Dataset (LungCapData): (https://bit.ly/2rOfgEJ);
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In this R video tutorial, we will learn how to modify and customize plots produced in R to make them look more beautiful! Here we will play around with the plots by changing the size of the plotting characters and fonts, changing the colours in plots, adding a regression line, making different groups stand out by using different colors and plotting characters, producing multiple plots on one screen, removing lables from axes and relabeling them, and more. Here we will learn how to use R functions such as "plot", "cex", "pch", "axis", "par", "mfrow", "col", “font”, and many more.
Table of Content:
0:00:31 how to access help menu in R for different plotting parameters using "par" command
0:01:00 how to change the size of the plotting characters in R using the "cex" argument
0:01:24 how to change the size of the title of a plot in R using the "cex.main" argument
0:01:36 how to change the size of the x and y labels of a plot in R using the "cex.lab" argument
0:01:51 how to change the size of the x and y axes values using "cex.axis" argument
0:02:16 how to change the fonts of the title of a plot in R using the "font.main" argument
0:02:45 how to change the font of the x or y labels of a plot in R using the "font.lab" argument
0:02:58 how to change the fonts of the x and y axis of a plot in R using the "font.axis" argument
0:03:21 how to change the colour of the plotting characters in R using the "col" argument
0:03:39 how to change the colour of the title of a plot in R using the "col.main" argument
0:03:48 how to change the color of the x and y labels of a plot in R using the "col.lab" argument
0:03:56 how to change the color of the x and y axis of a plot in R using the "col.axis" argument
0:04:26 how to change the plotting character in R using the "pch" argument
0:05:03 how to add a regression line to a plot in R using the "abline" command and change the line colour (using "col" argument), the line type (using "lty" argument) and the width of the line (using "lwd" argument)
0:05:45 how to identify different groups on the same plot (eg. male or female) using different plotting characters and colours
0:06:39 how to re-label x-axis and y-axis using the "xlab" and "ylab" arguments
0:07:05 how to add more points or observations to an existing plot using the "points" command
0:07:53 how to produce multiple plots on one screen in R using "mfrow" or "mfcol" arguments
0:10:10 how to re-label the axes of a plot in R
0:10:39 how to remove labels from x or the y-axis using the "axes" argument
0:11:47 how to re-label the x or y axis using the "side" argument and "axis" command
0:13:38 how to add a box around the plot in R using the "box" command
0:13:53 how to add values on top of the plot or on the right side of the plot in R using the "axis" command and "side" argument
These video tutorials are useful for anyone interested in learning data science and statistics with R programming language using RStudio.
► ► Watch More:
► Intro to Statistics Course: https://bit.ly/2SQOxDH
►Data Science with R https://bit.ly/1A1Pixc
►Getting Started with R (Series 1): https://bit.ly/2PkTneg
►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg
►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI
►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi
►Linear Regression in R (Series 5): https://bit.ly/1iytAtm
►ANOVA Concept and with R https://bit.ly/2zBwjgL
►Hypothesis Testing: https://bit.ly/2Ff3J9e
►Linear Regression Concept and with R Lectures https://bit.ly/2z8fXg1
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Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC.
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These videos are created by #marinstatslectures to support some courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free.
Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!