Dataset: Ukraine Invasion Refugee Data 2022

About this Dataset

Ukraine Invasion Refugee Data 2022

Context

The Russian invasion of Ukraine started on February 24, 2022. Attacks by Russian forces were reported in major cities across Ukraine, including Berdyansk, Chernihiv, Kharkiv, Odesa, Sumy, and the capital Kyiv. Western officials claimed that by scope, the war could be the largest in Europe since 1945. The Office of the United Nations High Commissioner for Human Rights (OHCHR) verified over 5.7 thousand deaths of civilians in Ukraine during the war as of September 2022.

The invasion caused Europe's largest refugee crisis since World War II, with over 7.2 million Ukrainians fleeing the country and a third of the population displaced. The refugees of the war mostly fled to the neighboring countries of Ukraine located in Central and Eastern Europe, prominently the nations of Poland, Hungary, Romania, Slovakia, Belarus, Republic of Moldova and Russia as well. With the situation in the regions of Ukraine changing, it is important to keep a general record regarding where the refugees are located, to provide better assistance to them and the concerned authorities.

About the dataset

This dataset contains information about the number of Ukrainian refugees that a neighboring country is housing at different points in time, starting from early March. The countries that mostly feature in the data are obviously the ones mentioned before that share borders with the nation of Ukraine. Each record mentions the country, the date of recording, the number of refugees in that country, and geospatial data of the particular region which could help in some useful geographical analysis. The consecutive entries for one country seem to be not more than a week apart at any given time. United Nations High Commissioner for Refugees (UNHCR) and local governments are the main sources.

This file was extracted using an API about war data from RapidAPI. I will also provide regular updates to this dataset whenever I find any. I am still new to this technique of extraction so any feedback would be highly appreciated.

Inspiration

The war has inflicted large scale damage on many different communities and I believe the data science community has the knowledge and resources of providing help. I believe all data enthusiasts learn about data science to help in solving real world problems that society faces and providing aid during times of humanitarian crises would be influential work of the highest order.

Visit this link if you wish to donate or provide other support to the efforts in Ukraine:
https://stand-with-ukraine.pp.ua/

Tables

Ukr Refugee By Countries 1

@kaggle.anuragbantu_ukraine_invasion_refugee_data_2022.ukr_refugee_by_countries_1

23.85 KB
665 rows
12 columns


CREATE TABLE ukr_refugee_by_countries_1 (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "country" VARCHAR,
  "date" TIMESTAMP,
  "individuals" BIGINT,
  "centroid_lon" DOUBLE,
  "centroid_lat" DOUBLE,
  "lat_max" DOUBLE,
  "lon_max" DOUBLE,
  "lan_min" DOUBLE,
  "lon_min" DOUBLE,
  "source" VARCHAR
);

Ukr Refugee By Countries 2

@kaggle.anuragbantu_ukraine_invasion_refugee_data_2022.ukr_refugee_by_countries_2

23.95 KB
671 rows
12 columns


CREATE TABLE ukr_refugee_by_countries_2 (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "country" VARCHAR,
  "date" TIMESTAMP,
  "individuals" BIGINT,
  "centroid_lon" DOUBLE,
  "centroid_lat" DOUBLE,
  "lat_max" DOUBLE,
  "lon_max" DOUBLE,
  "lan_min" DOUBLE,
  "lon_min" DOUBLE,
  "source" VARCHAR
);

Ukr Refugee By Countries

@kaggle.anuragbantu_ukraine_invasion_refugee_data_2022.ukr_refugee_by_countries

23.75 KB
659 rows
12 columns


CREATE TABLE ukr_refugee_by_countries (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "country" VARCHAR,
  "date" TIMESTAMP,
  "individuals" BIGINT,
  "centroid_lon" DOUBLE,
  "centroid_lat" DOUBLE,
  "lat_max" DOUBLE,
  "lon_max" DOUBLE,
  "lan_min" DOUBLE,
  "lon_min" DOUBLE,
  "source" VARCHAR
);