CURATING DATASETS IS TIME CONSUMING AND DIFFICULT, SO IF YOU FIND THE CONTENT USEFUL, PLEASE LEAVE AN UPVOTE! THANK YOU! 🙏

This is what real world data looks like! It is often messy, complicated, and leaves you wondering what you can even do with it. That is the fun and difficulty of data science. You have information, but what can you do with it? Should you try to use machine learning? Should you use statistics? That is for you to find out! 😄

About the Dataset

This dataset contains information regarding the ongoing Ukrainian and Russian conflict data dating back to 2014. There are two CSV files in this dataset. One contains data from 2014 to 2021, the other contains data from 2018 to 2023. Use your data science skills to better understand a conflict that is happening in real time! This is an excellent project for those looking to better understand global events or who are looking to work on a dataset with greater implications and a larger impact than a cat vs. dog classifier. 👍

I will be contributing to this dataset as new data becomes available, so stay tuned!

About the Conflict

The Ukraine-Russia conflict began in 2014 when Russia annexed Crimea from Ukraine, but the history of these two nations goes back much further than 2014. Since then, pro-Russian separatists have been fighting Ukrainian government forces in the Donbas region of Eastern Ukraine. The conflict has resulted in thousands of deaths and the displacement of over 1.5 million people.

In 2022, the conflict escalated again, with Russia mobilizing its military near the Ukrainian border and launching a large-scale invasion in February. Ukrainian forces have been engaged in heavy fighting with Russian troops and separatist militias, resulting in a humanitarian crisis and significant civilian casualties.

The international community has condemned Russia's actions and imposed economic sanctions on the country. Diplomatic efforts to resolve the conflict, including negotiations and ceasefires, have not been successful so far. The conflict remains ongoing and the situation is highly volatile.

Tables

Conflict Data Ukr

@kaggle.kylegraupe_ukrainerussia_conflict_dataset.conflict_data_ukr

342.37 KB
2990 rows
50 columns


CREATE TABLE conflict_data_ukr (
  "id" DOUBLE,
  "relid" VARCHAR,
  "year" VARCHAR,
  "active_year" DOUBLE,
  "code_status" VARCHAR,
  "type_of_violence" DOUBLE,
  "conflict_dset_id" DOUBLE,
  "conflict_new_id" DOUBLE,
  "conflict_name" VARCHAR,
  "dyad_dset_id" DOUBLE,
  "dyad_new_id" DOUBLE,
  "dyad_name" VARCHAR,
  "side_a_dset_id" DOUBLE,
  "side_a_new_id" DOUBLE,
  "side_a" VARCHAR,
  "side_b_dset_id" DOUBLE,
  "side_b_new_id" DOUBLE,
  "side_b" VARCHAR,
  "number_of_sources" DOUBLE,
  "source_article" VARCHAR,
  "source_office" VARCHAR,
  "source_date" VARCHAR,
  "source_headline" VARCHAR,
  "source_original" VARCHAR,
  "where_prec" DOUBLE,
  "where_coordinates" VARCHAR,
  "where_description" VARCHAR,
  "adm_1" VARCHAR,
  "adm_2" VARCHAR,
  "latitude" VARCHAR,
  "longitude" VARCHAR,
  "geom_wkt" VARCHAR,
  "priogrid_gid" DOUBLE,
  "country" VARCHAR,
  "iso3" VARCHAR,
  "country_id" DOUBLE,
  "region" VARCHAR,
  "event_clarity" DOUBLE,
  "date_prec" DOUBLE,
  "date_start" VARCHAR,
  "date_end" VARCHAR,
  "deaths_a" DOUBLE,
  "deaths_b" DOUBLE,
  "deaths_civilians" DOUBLE,
  "deaths_unknown" DOUBLE,
  "best" VARCHAR,
  "high" DOUBLE,
  "low" DOUBLE,
  "gwnoa" DOUBLE,
  "gwnob" VARCHAR
);

Ukraineconflict

@kaggle.kylegraupe_ukrainerussia_conflict_dataset.ukraineconflict

5.09 MB
96082 rows
31 columns


CREATE TABLE ukraineconflict (
  "event_id_cnty" VARCHAR,
  "event_date" VARCHAR,
  "year" BIGINT,
  "time_precision" BIGINT,
  "disorder_type" VARCHAR,
  "event_type" VARCHAR,
  "sub_event_type" VARCHAR,
  "actor1" VARCHAR,
  "assoc_actor_1" VARCHAR,
  "inter1" BIGINT,
  "actor2" VARCHAR,
  "assoc_actor_2" VARCHAR,
  "inter2" BIGINT,
  "interaction" BIGINT,
  "civilian_targeting" VARCHAR,
  "iso" BIGINT,
  "region" VARCHAR,
  "country" VARCHAR,
  "admin1" VARCHAR,
  "admin2" VARCHAR,
  "admin3" VARCHAR,
  "location" VARCHAR,
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "geo_precision" BIGINT,
  "source" VARCHAR,
  "source_scale" VARCHAR,
  "notes" VARCHAR,
  "fatalities" BIGINT,
  "tags" VARCHAR,
  "timestamp" BIGINT
);