R- Basics Class III

1 Shortcuts in R

Today we will discuss 6 nos of shortcuts in R-studio

Clear the consol : ctrl/control + L both in Windows and Mac
Move the cursor to Consol : ctrl/control + 2 both in Windows and Mac
Piping operator in tidyverse : ctrl + shift + M in Windows and cmd + shift + M in case of Mac
assign operator in R : alt + - in Windows and option + - in Mac
Move cursor to beginning of the line : home in Windows and Cmd + Left arrow in Mac
Move the cursor to end of the line: end in Windows and cmd + Right arrow in Mac

2 How to change the the colour of the code in the source pane

We can change the colour in the source pane of R Studio by using Tools then Global Options and then Appearance then Editor theme and select the schema you are interested in, I am using Textmate.

for rainbow colour , click in the Global option , then click code , then click on display and then tick mark and then in indention guide select Rainbow fills and in syntax, tick the rainbow parentheses like the screenshot below

3 How to bring the data to R

Suppose your file is in excel and you want to bring the excel file to RStudio for further analysis

First create a project in R-Studio by clicking file, then New Project.., then New Directory, then New Project, then browse and create a new folder test2 in mydocument folder and select the folder then create the project. Now you can see a test2.Rproj file in the test2 folder.
Now copy your excel file in the test2 folder .
Now click on the project file and open and open a new Rscript in the source pane by click on on file then on New File and then on R Script .
Let us import the excel file form the folder.
Now click on the import button on the Environment pane (2nd row and third button), and select from Excel.. , then click on browse and select the folder and the excel file, then click on open . you will find a page like below - (fig. 1)

Now we change the name from the Name section, we can give any name, here we will give my_data
In the Sheet, default is the default sheet, generally the first sheet. However, one can change the sheet they are interested in.
In the Range section, one can select the range of the data, he/she interested in .
In the max row section, one can provide the maximum rows one is interested in.
In skip section, one can provide the number of rows to be skipped (like1 or 2 or 3 etc..)
In NA section any character to be named as NA, has to be given, for example in this data set we have 2 number of ** , so we will provide 2 stars ** in the that section to change all the starts into NA.
Below the code preview section, one can click to import or copy the codes and paste in the R script in the source pane.

library(tidyverse)# must call tidyverse package

Warning: package 'ggplot2' was built under R version 4.3.3

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(readxl) # this is a package to import excel files and if the package is not installed yet, then kindly install it by - install.packages ("readxl")

my_data<- read_excel("Number of Fishers by site.xlsx",sheet = "2023", col_types = c("text", "numeric", "numeric", "numeric"))

Warning: Expecting numeric in B3 / R3C2: got '**'

Warning: Expecting numeric in D8 / R8C4: got '**'

Warning: Expecting numeric in D12 / R12C4: got '**'

summary(my_data)

 Operating SITE       Full Time        Part Time        Temporary  
 Length:17          Min.   :  4.00   Min.   : 0.000   Min.   :0.0  
 Class :character   1st Qu.:  5.50   1st Qu.: 0.000   1st Qu.:0.0  
 Mode  :character   Median : 20.00   Median : 1.500   Median :0.0  
                    Mean   : 35.87   Mean   : 2.625   Mean   :0.4  
                    3rd Qu.: 34.50   3rd Qu.: 2.000   3rd Qu.:0.5  
                    Max.   :269.00   Max.   :21.000   Max.   :3.0  
                    NA's   :2        NA's   :1        NA's   :2

Now you can see the summary statistics of the data. it will provide the Minimum value, maximum value, 1st quartile, median , mean, 3rd quartile value and number of NAs in the data.

4 To make a bardiagram of full time fisher

my_data %>% 
  ggplot(aes(x= `Operating SITE`, y = `Full Time`)) +
  geom_col() +
  labs(y = "Full time Fishers", x = "Sites") +
  theme(axis.text = element_text(face="bold")) +
  theme(axis.text.x = element_text(angle = 90))

Warning: Removed 2 rows containing missing values or values outside the scale range
(`geom_col()`).

5 How to make the graph colourful

5.1 Fill the bars with clour “steelblue”

my_data %>% 
  ggplot(aes(x= `Operating SITE`, y = `Full Time`)) +
  geom_col(fill ="steelblue") +
  labs(y = "Full time Fishers", x = "Sites") +
  theme(axis.text = element_text(face="bold")) +
  theme(axis.text.x = element_text(angle = 90))

Warning: Removed 2 rows containing missing values or values outside the scale range
(`geom_col()`).

5.2 Colour the boarder of the bars

5.2.1 only boarder of bars with “steelblue” and inside the bars filled with white colour

my_data %>% 
  ggplot(aes(x= `Operating SITE`, y = `Full Time`)) +
  geom_col(colour = "steelblue", fill = "white") +
  labs(y = "Full time Fishers", x = "Sites") +
  theme(axis.text = element_text(face="bold")) +
  theme(axis.text.x = element_text(angle = 90))

Warning: Removed 2 rows containing missing values or values outside the scale range
(`geom_col()`).