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# install the package
install.packages("RMySQL") 


# load the package
library(RMySQL)


# create a MySQL connection object
con <- dbConnect(MySQL(),

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# load packages
library(olsrr)
#> 
#> Attaching package: 'olsrr'
#> The following object is masked from 'package:datasets':
#> 
#>     rivers

# regression

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import numpy as np

# create two dimensional arrays
np1 = np.arange(0, 9).reshape(3, 3)
np1

np2 = np1 * 5
np2

# horizontal stacking

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# install
install.packages('ggplot2')
install.packages('readr')

# load
library(ggplot2)
library(readr)

# Scatter Plot
p <- ggplot(mtcars) +

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# Case Study 1: combine 4 plots in 2 rows and 2 columns
# store the current parameter settings in init
init <- par(no.readonly=TRUE)
 
# specify that 4 graphs to be combined and filled by rows
par(mfrow = c(2, 2))
 
# specify the graphs to be combined
plot(mtcars$mpg)
plot(mtcars$disp, mtcars$mpg)

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# text inside plot
plot(mtcars$disp, mtcars$mpg)
text(x = 340, y = 30, labels = 'Sample Text')

# color
plot(mtcars$disp, mtcars$mpg)
text(x = 340, y = 30, labels = 'Sample Text', col = 'red')

# font
plot(mtcars$disp, mtcars$mpg)

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# data
year <- seq(2010, 2014, 1)
india <- c(10.3, 6.6, 5.6, 6.6, 7.2)
china <- c(10.6, 9.5, 7.8, 7.7, 7.3)
russia <- c(4.5, 4.3, 3.5, 1.3, 0.7)
brazil <- c(7.5, 3.9, 1.9, 3.0, 0.1)
s_africa <- c(3.2, 3.2, 2.2, 2.2, 1.5)
gdp <- data.frame(year, india, china, russia, brazil, s_africa, stringsAsFactors = FALSE)
gdp

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# distributions
# normal distribution
hist(rbeta(10000, 5, 5), ann = FALSE, col = 'blue')

# skewed distributions
hist(rbeta(10000, 2, 5), ann = FALSE, col = 'blue')
hist(rbeta(10000, 5, 2), ann = FALSE, col = 'blue')

# histogram
# store the results of hist function

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# basic plot
boxplot(mtcars$mpg)

# horizontal box plot
boxplot(mtcars$mpg, horizontal = TRUE)

# color
boxplot(mtcars$mpg, col = 'blue')

# border color

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# using plot function
plot(as.factor(mtcars$cyl))

# using bar plot function
barplot(table(mtcars$cyl))

# tabulated data
cyl_freq <- table(mtcars$cyl)
cyl_freq