Dossier on the Election in the Lab

Dossier on the election available in the Lab -a collection of election information from our site. All materials where this election is mentioned.

Election Cards

Database of NGO Golos Movement
External Sources Manager

Database of NGO Golos Movement

Machine-readable data library

The Golos Movement collects and processes data from the Central Election Commission of Russia for easy analysis. The Movement's database contains data on more than one hundred thousand elections at various levels in the Russian Federation.

Data format:

*.csv in *.zip archives.

Parsing time:

As a rule, automatically three-four days after publication or upon request. 

Disadvantages noted:

Superfluous lines when commissions change the structure of PECs before and after the election. Digital PECs are not parsed (as of summer 2020).

Digital PECs are not parsed (as of summer 2020).
Instructions:

Go to «Election Calendar», find the elections you need

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and on the page that opens, follow the link to download the zip archive with the results.

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Articles on the Elections

Azat Gabdulvaleev "Analysis of election results in the city of Grozny using graphical visualization and turnout counting based on video recordings from polling stations"

Presentation at the II Round Table of Mathematicians

Azat Gabdulvaleev 0 16762

Azat Gabdulvaleev "Analysis of election results in the city of Grozny using graphic visualization and turnout counting based on video recordings from polling stations

The subject of the study is the capital of the Chechen Republic - the city of Grozny. It should be said that Chechnya consistently shows superloyal results in elections at any level.

Azat Gabdulvaleev "Graphical visualization of open data as a simple way to detect anomalies in voting results"

Presentation at the II Round Table of Mathematicians

Azat Gabdulvaleev 0 11951

One such method is graphical visualization of open data. There is little or no math involved, but the charts can immediately identify some anomalies and indicate areas that need more detailed investigation.

So you can visualize open data in a graphical way.

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