University : University of Canberra UniLearnO is not sponsored or endorsed by this college or university.
Country : Australia
Assignment Task :

 
Motivation The purpose of this assignment is to assess your skills on reading multiple data files, merging them into a single data frame, applying different cleaning and wrangling steps and then getting the data ready for the modelling. 
 

Data Description The observations in the attached CSV files have been taken from the Bureau of Meteorology's "real time" system. These observations provide some details about the weather in the Australian Capital territory for 19 months. Most of the data are generated automatically. Some quality checking has been performed, but it is still possible for erroneous values to appear. Sometimes, when the daily maximum and minimum temperatures, rainfall or evaporation are missing, the next value given has been accumulated over several days rather than the normal one day. There are 19 comma-separated data files provided with this assignment. These data are for the months from August 2018 to February 2020. The variables reported in each file are described in Table I. 
 

Day

 

Copyright of the Data Copyright of Bureau of Meteorology materials resides with the Commonwealth of Australia. Apart from any fair dealing for purposes of study, research, criticism and review, as permitted under copyright legislation, no part of this product may be reproduced, re-used or redistributed for any commercial purpose whatsoever, or distributed to a third party for such purpose, without written permission from the Director of Meteorology. 
 

Tasks  Part A, Reading First, you have 19 CSV files and you need to write R code to

1- Load these files into your working directory, one by one.

2- Concatenate all the data of these files into one data frame. You may use loop statement to achieve that. It is recommended to use the functions from the 'ficlyverse. package to read and to import these files. However, using any of the other functions are also fine.

3- Check for problems while loading and parsing the data. 

 

Part B - Preparing (For UG and G students) Write code to do the following tasks

1- Remove the variables, which have no data at all (i.e. all the records in these variables are NAs)

2- Drop the variables, which have few data (i.e. NAs values are more than 90% of number of records in these variables).

3- Change the column names to have no spaces between the words and replace these spaces with underscore the `: character.

4- Change the type of the column called "Date" from character to Date data type.

5- Add two new columns for the month and year of the data in each file, you may extract the contents of this column from the "Date" column. Please note that the data are collected for 19 months across 3 years (2018, 2019 and 2020).

6- Change the type of the "Month" and "Year" columns from Character to Ordinal with levels as the number of months in a year (i.e. 12) and number of years (3).

7- For all the numeric columns, replace the remaining NAs with the median of the values in the column, if exist. 

 

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  • Uploaded By : Grace
  • Posted on : December 02nd, 2018
  • Downloads : 185

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