MATH2349: Data Preprocessing- R Functions- R Studio- Report writing Assignment

Internal Code: MAS7284

Report writing Assignment:

Task: 1- Locate an open source of data from the web. This can be a tabular, spreadsheet data (i.e., .txt, .csv, .xls, .xlsx files), data sets from other statistical software (i.e., SPSS, SAS, Stata etc. data files), or you can scrape HTML table data. Some sources for open data are provided below, but I encourage you to find others: 1. http://www.abs.gov.au/ 2. https://www.data.vic.gov.au/ 3. http://www.bom.gov.au/ 4. https://www.kaggle.com As a minimum, the data set should include: ? one numeric variable. ? one qualitative (categorical) variable. There is no limit on the number of observations and number of variables. But keep in mind that when you have a very large data set, it will increase your reading time. 2- Read/Import the data into R, then save it as a data frame. You can use Base R functions or readr, xlsx, readxl, foreign, rvest packages for this purpose. 3- Inspect the data frame and variables using R functions. As a minimum, you should: ? check the dimensions of the data frame. ? check the data types (i.e., character, numeric, integer, factor, and logical) of the variables in the data set. ? check the levels of factor variables, rename/rearrange them if required. ? check the column names in the data frame, rename them if required. 4- Subset the data frame using first 10 observations (include all variables). Then convert it to a matrix. If you get an error, explain why you got this error. 5- Subset the data frame including only first and the last variable in the data set, save it as an R object file (.RData).