Lab 8

Rmd

School

Missouri University of Science & Technology *

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Course

3420

Subject

Information Systems

Date

Dec 6, 2023

Type

Rmd

Pages

2

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--- title: "Lab 8" output: html_document date: "2022-11-03" editor_options: chunk_output_type: console --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ```{r} rm(list = ls()) ``` #1 Read the cleansed data set into R ```{r} library(jsonlite) weblog <- stream_in(file("weblog_clean.jsonlines")) ``` #2 Show the structure of the data set ```{r} str(weblog) ``` #3 Change the data type ```{r} x <- as.POSIXct(weblog$request.datetime, tz="", format = "%Y-%m-%d %H:%M:%OS") weblog$request.datetime <- x ``` #4 Show the summary statistics of the data set ```{r} summary(weblog) ``` #5 Get the frequency distribution of 'weekday' ```{r} table(weblog$weekday) #Wednesday has the largest number of visits. ``` #6 Cross tabulate 'weekday' and 'request.uri' ```{r} table(weblog$weekday, weblog$request.uri) #There are 4407 visits on the 'faq.html' page on Fridays. ``` #7 Draw a bar plot to show the distribution of visits by 'weekday' ```{r} weekday.dist <- table(weblog$weekday) barplot(weekday.dist)
``` #8 Draw a stacked bar plot to show the distribution of visits by 'request.uri' and 'request.method' ```{r} weblog.stackedbarplot <- table(weblog$request.method, weblog$request.uri) barplot(weblog.stackedbarplot, main = "Distribution of Visits", xlab = "Type of URI Request", ylab = "Number of Request", col = rainbow(2), legend = rownames(weblog.stackedbarplot)) ``` #9 Draw a pie chart to present the distribution of visits by 'request.uri' and show the count of visits for each URI ```{r} ruri.dist <- table(weblog$request.uri) lb1 <- paste(names(ruri.dist), ruri.dist, sep=" ") pie(ruri.dist, labels = lb1, main="Pie Chart of 'request.uri' Distribution (with number of visits)", col=rainbow(length(lb1))) ``` #10 Draw a pie chart to present the distribution of visits by 'request.uri' and how the percentage of visits for each URI ```{r} pct <- round(ruri.dist/sum(ruri.dist)*100, digits = 1) lb2 <- paste(names(ruri.dist), "visits ", sep=" ", paste(pct,"%")) pie(ruri.dist, labels = lb2, main="Pie Chart of 'request.uri' Distribution (with percentage)", col=rainbow(length(lb2))) ``` #11 Calculate 5-number summary for 'reponse.size' ```{r} quantile(weblog$response.size, type=7) ``` #12 Knit R Markdown file into an HTML file
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