Data
Movinga-Best-Cities-for-Families-2019

Movinga-Best-Cities-for-Families-2019

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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  • Computer Systems Machine Learning
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Context This data was scraped from Movinga (https://www.movinga.com/), the global moving company and determines the top cities around the world that offer the best conditions to raise a family for 2019. The dataset was extended to add geographical location in terms of the latitude and longitude of the city. The original data can be found here. From their website: "We began the study by selecting 150 international cities that have a reputation as attractive locations for raising a family. We then split the study into numerous factors across three categories which indicate how family-friendly a location is. This included essentials that affect city livability like housing, education, employment rates, and general affordability, as well as family legislation such as the amount of paid parental leave and whether a city is inclusive for same-sex parents. It was important to include the opinions of the families who experience these cities themselves, so we commissioned two surveys of parents in each location to gain a measurement of public sentiment towards them. The first survey asked parents to indicate how they felt about their childrens safety in the community, and the second if they believed that their city was a good place for families in general. Last but not least, we looked at the attractiveness and breadth of a citys family-oriented leisure activities. The final index combines all of these factors to determine the top cities around the world that offer the best conditions to raise a family." Content This data was scraped from Movinga (https://www.movinga.com/), the global moving company. The original data can be found here. The data includes 18 columns: City Country Housing Affordability Living Costs by Income Unemployment () Education Safety Mobility Air Quality (g/m3) Healthcare Kids' Activities Paid Parental Leave (Days) Family Inclusivity Neighbourhood Safety Family-Friendliness Total Latitude Longitude Note that all factors are scored out of 100 (unless noted otherwise above) where the higher the score, the better. Further, the score for these factors was calculated by applying a mix-max normalisation to the underlying indicator. For further details of the scoring and methodology of the study, please refer to https://www.movinga.de/en/cities-of-opportunity-for-families. Acknowledgements I'd like to thank Movinga for providing the original data on their website.

18 features

Citystring150 unique values
0 missing
Countrystring47 unique values
0 missing
Housing_Affordabilitynumeric148 unique values
0 missing
Living_Costs_by_Incomenumeric149 unique values
0 missing
Unemploymentnumeric125 unique values
0 missing
Educationnumeric98 unique values
0 missing
Safetynumeric96 unique values
0 missing
Mobilitynumeric149 unique values
0 missing
Air_Qualitynumeric141 unique values
0 missing
Healthcarenumeric150 unique values
0 missing
Kids_Activitiesnumeric149 unique values
0 missing
Paid_Parental_Leavenumeric44 unique values
0 missing
Family_Inclusivitynumeric17 unique values
0 missing
Neighbourhood_Safetynumeric44 unique values
0 missing
Family-Friendlinessnumeric34 unique values
0 missing
Totalnumeric145 unique values
0 missing
Latnumeric150 unique values
0 missing
Longnumeric150 unique values
0 missing

19 properties

150
Number of instances (rows) of the dataset.
18
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
16
Number of numeric attributes.
0
Number of nominal attributes.
0.12
Number of attributes divided by the number of instances.
88.89
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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