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Jan

Whether you're working with large datasets or small samples, R programming can help you create clear and effective visualizations that c.....

Jan

data<- read.csv(file = "C:\\Users\\dell\\Downloads\\GHQ1(2).csv") library("ggplot2") library("dplyr") head(data) View(data) da.....

Dec

data<- read.csv(file = "C:\\Users\\dell\\Downloads\\GHQ1(2).csv") library("ggplot2") library("dplyr") head(data) View(data) data_so2.....

Dec

setwd("~/Assignments/Job 2") rm(list = ls()) # Load libraries: library(reshape2) library(ggpubr) # Read the data: data <- read......

Dec

```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) options(warn = -1) ``` ## 1. Provide appropriate graphs to display freq.....

Nov

review_data_toys_and_games <-read.table("Toys_and_Games_5.json", header = FALSE, sep = '\t', quote = "\"", stringsAsFactors = FAL.....

Nov

library(DBI) library(RSQLite) if (exists("myDB")) { dbDisconnect(myDB) } myDB <- dbConnect(drv = RSQLite::SQLite(), dbname = "c.....

Nov

```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ## Importing libraries ```{r} library(readxl) library(strucchange.....

Nov

# DIGIT RECOGNIZER # rm(list = ls()) set.seed(1001) setwd("~/Assignments/Job 1") library(data.table) library(FNN) library(caret).....