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https://github.com/emaasit/ugvoters16
An R package for the counts of Ugandan registered voters for the 2016 General Election
https://github.com/emaasit/ugvoters16
Last synced: about 1 month ago
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An R package for the counts of Ugandan registered voters for the 2016 General Election
- Host: GitHub
- URL: https://github.com/emaasit/ugvoters16
- Owner: Emaasit
- Created: 2016-02-12T03:14:16.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2016-02-13T23:10:25.000Z (almost 9 years ago)
- Last Synced: 2023-02-27T18:03:39.702Z (over 1 year ago)
- Language: HTML
- Size: 11 MB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: ReadMe-file.html
Awesome Lists containing this project
README
Counts of Ugandan registered voters for the 2016 General Election
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Counts of Ugandan registered voters for the 2016 General Election
Daniel Emaasit
February 11, 2016
UGvoters16
What is this?
UGvoters16 is a package for the counts of Ugandan registered voters for the 2016 presidential election provided by the Electoral Commision (EC) of Uganda. This package contains the number of registered voters by polling station. This “controversial” data was claimed to contain atleast 20,000 “ghost voters” by members of the Ugandan media because the total count from the each polling station are not equal to the totals reported by the Electoral Commission.
How to use it
Before you can use the data in R, you need to download it from Github using the following commands:
installed.packages("devtools")
## Package LibPath Version Priority Depends Imports LinkingTo Suggests
## Enhances License License_is_FOSS License_restricts_use OS_type Archs
## MD5sum NeedsCompilation Built
devtools::install_git("git://github.com/emaasit/UGvoters16.git", branch = "master")
library(UGvoters16)
After loading the library, you can create a local data frame using the following command:
df1 <- UGvoters16
df2 <- analyzed
head(df1)
## SER_NO DIST_CODE DISTRICT_NAME EA_CODE EA_NAME SCTY_CODE
## 1 1 01 APAC 002 KWANIA COUNTY 01
## 2 2 01 APAC 002 KWANIA COUNTY 01
## 3 3 01 APAC 002 KWANIA COUNTY 01
## 4 4 01 APAC 002 KWANIA COUNTY 01
## 5 5 01 APAC 002 KWANIA COUNTY 01
## 6 6 01 APAC 002 KWANIA COUNTY 01
## SCOUNTY_NAME PAR_CODE PARISH_NAME PS_CODE PS_NAME
## 1 ADUKU 01 ADYEDA 01 ADYEDA CENTRE
## 2 ADUKU 01 ADYEDA 02 APORWEGI P.7 SCHOOL
## 3 ADUKU 01 ADYEDA 03 ADYEDA IMALO
## 4 ADUKU 02 ALIRA 01 ALIRA B
## 5 ADUKU 02 ALIRA 02 AKOT A
## 6 ADUKU 02 ALIRA 03 OLEKE
## NO_OF_FEMALES NO_OF_MALES EC_VOTER_COUNTS ANALYZED_VOTER_COUNT
## 1 134 143 277 277
## 2 379 323 703 702
## 3 164 157 322 321
## 4 461 411 872 872
## 5 386 364 750 750
## 6 443 383 826 826
head(df2)
## SER_NO DIST_CODE DISTRICT_NAME EA_CODE EA_NAME SCTY_CODE
## 1 1 1 APAC 2 KWANIA COUNTY 1
## 2 2 1 APAC 2 KWANIA COUNTY 1
## 3 3 1 APAC 2 KWANIA COUNTY 1
## 4 4 1 APAC 2 KWANIA COUNTY 1
## 5 5 1 APAC 2 KWANIA COUNTY 1
## 6 6 1 APAC 2 KWANIA COUNTY 1
## SCOUNTY_NAME PAR_CODE PARISH_NAME PS_CODE PS_NAME
## 1 ADUKU 1 ADYEDA 1 ADYEDA CENTRE
## 2 ADUKU 1 ADYEDA 2 APORWEGI P.7 SCHOOL
## 3 ADUKU 1 ADYEDA 3 ADYEDA IMALO
## 4 ADUKU 2 ALIRA 1 ALIRA B
## 5 ADUKU 2 ALIRA 2 AKOT A
## 6 ADUKU 2 ALIRA 3 OLEKE
## NO_OF_FEMALES NO_OF_MALES EC_VOTER_COUNTS ANALYZED_VOTER_COUNT
## 1 43 51 240 277
## 2 312 251 687 702
## 3 76 66 287 321
## 4 404 349 869 872
## 5 320 296 739 750
## 6 384 317 819 826
What can you do with it?
You can explore for yourself and see why the Ugandan media claimed it has atleast 20,000 “ghost voters”.
Example Analysis
How many voters are registered
# what are the column names
names(df1)
## [1] "SER_NO" "DIST_CODE" "DISTRICT_NAME"
## [4] "EA_CODE" "EA_NAME" "SCTY_CODE"
## [7] "SCOUNTY_NAME" "PAR_CODE" "PARISH_NAME"
## [10] "PS_CODE" "PS_NAME" "NO_OF_FEMALES"
## [13] "NO_OF_MALES" "EC_VOTER_COUNTS" "ANALYZED_VOTER_COUNT"
names(df2)
## [1] "SER_NO" "DIST_CODE" "DISTRICT_NAME"
## [4] "EA_CODE" "EA_NAME" "SCTY_CODE"
## [7] "SCOUNTY_NAME" "PAR_CODE" "PARISH_NAME"
## [10] "PS_CODE" "PS_NAME" "NO_OF_FEMALES"
## [13] "NO_OF_MALES" "EC_VOTER_COUNTS" "ANALYZED_VOTER_COUNT"
# count the total number of analyzed voter counts
sum(df2$ANALYZED_VOTER_COUNT)
## [1] 15277197
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