Using Exploratory Data Analysis Techniques in the 2016 USA Presidential Campaign Finance in the State of California
The project uses exploratory data analysis techniques (EDA) to explore the 2016 Presidential Campaign Finance contributions dataset. The analysis is restricted to the State of California. The purpose of the EDA is to understand the contributors behaviour during presidential campaigns. The analysis was conducted in R using the ggplot2 library.
- final_project.html: Knitted html file containing the analysis (final presentation).
- final_project.Rmd: File containing the EDA description and R script.
- P00000001-CA.csv.zip: A zipped file containing the contributions data for the State of California.
- CONTRIBUTOR_FORMAT.txt: Contains a dictionary of all the fields in the dataset
- california_cities.csv: Contains the coordinates of each of the major cities in the State of California.
- zipcodes_2013.txt: Coordinates for each of the zip codes in the USA.
-
Loading Data and Basic Formatting in R: http://flowingdata.com/2015/02/18/loading-data-and-basic-formatting-in-r/
-
RStudio Cheat Sheets: https://www.rstudio.com/resources/cheatsheets/
-
How to draw good looking maps in R: https://uchicagoconsulting.wordpress.com/tag/r-ggplot2-maps-visualization/
-
Making Maps with R: http://eriqande.github.io/rep-res-web/lectures/making-maps-with-R.html
-
Predicting Gender Using Historical Data: https://cran.rstudio.com/web/packages/gender/vignettes/predicting-gender.html
-
Regular Expression in R: http://stat545.com/block022_regular-expression.html
-
Joining 2 R data sets with different column names: https://www.r-bloggers.com/joining-2-r-data-sets-with-different-column-names/
-
Extract Month and Year From Date in R: https://stackoverflow.com/questions/37704212/extract-month-and-year-from-date-in-r
-
Date Values: http://www.statmethods.net/input/dates.html
-
Introduction to ggthemes: https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html