Visualization of analytical data to assess the quality of life of the population in large Russian cities

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The article describes the technology of using the Foursquare service, the folium library, as well as clustering techniques based on the k-means method for analyzing and assessing the quality of life of the population in large cities, where more than 100 thousand people live. The main indicators of the quality of life of the population of a particular city were selected data on migration flows, housing price, as well as the environmental situation. During the study, a hypothesis was determined about the direct dependence of the outflow of the urban population on the level of high cost of housing, as well as on the level of the ecological situation of a particular city. As a result of the analysis, a figurative relationship between the cost of housing and the outflow of the urban population was revealed – in cities with a high cost of housing the highest level of population growth. In addition, in cities where there is an outflow of urban population, along with a very low cost of housing, the highest level of environmental pollution was found. Also, clustering of cities using the k-means method showed that in cities with a high cost of housing and a high rate of population growth due to migration flows, a low level of environmental pollution was revealed. The capabilities of the folium library of the Python programming language made it possible to visually present an interactive map of the country with the level of the ecological situation of cities. According to the author, the results of such studies affect not only the formation of managerial decisions at the federal and regional levels, but also on the assessment of the attractiveness of the city for the life of the local population, as well as people planning to change their place of residence.