Corruption Perceptions Index

core

Files Size Format Created Updated License Source
2 113kB csv zip 1 week ago
corruption perceptions index the data is sourced from transparency international. > the corruption perceptions index (cpi) ranks countries/territories in terms of the degree to which corruption is perceived to exist among public officials and politicians. it draws on different assessments and read more
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Data Files

File Description Size Last changed Download Other formats
data [csv] 15kB data [csv] data [json] (63kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 20kB datapackage_zip [zip]

data  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
Jurisdiction 1 string (default)
1998 2 string (default)
1999 3 string (default)
2000 4 string (default)
2001 5 string (default)
2002 6 string (default)
2003 7 string (default)
2004 8 string (default)
2005 9 string (default)
2006 10 string (default)
2007 11 string (default)
2008 12 string (default)
2009 13 string (default)
2010 14 string (default)
2011 15 string (default)
2012 16 string (default)
2013 17 string (default)
2014 18 string (default)
2015 19 string (default)

datapackage_zip  

This is a preview version. There might be more data in the original version.

Read me

corruption perceptions index

the data is sourced from transparency international.

the corruption perceptions index (cpi) ranks countries/territories in terms of the degree to which corruption is perceived to exist among public officials and politicians. it draws on different assessments and business opinion surveys carried out by independent and reputable institutions. it captures information about the administrative and political aspects of corruption. broadly speaking, the surveys and assessments used to compile the index include questions relating to bribery of public officials, kickbacks in public procurement, embezzlement of public funds, and questions that probe the strength and effectiveness of public sector anti-corruption efforts.

more info here.

requires:

  1. r - rvest, xlsx
  2. java 8
  3. julia - gadfly, dataframes

note: the scale of the cpi is 0-10 from 1998 to 2011, and 0-100 from 2012 onwards, due to an update to the methodology used to calculate the cpi in 2012.

data in data/ generated by:

$ ./acquire_data.r

or, for the paranoid:

$ torify ./acquire_data.r

acquire_data.r downloads files from transparency international, converts them to csv format, and mergesthem in cpi.csv file.

warning: the files are not at all curated well. many countries are spelled different ways in each annual report, so the scripts will count them as different countries.

Import into your tool

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/core/corruption-perceptions-index/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources[[1]]$path
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/core/corruption-perceptions-index/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('http://datahub.io/core/corruption-perceptions-index/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'http://datahub.io/core/corruption-perceptions-index/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
(async () => {
  const dataset = await Dataset.load(path)

  // Get the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/core/corruption-perceptions-index/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json