The objective of this data analytics challenge was to identify and analyze an existing urban issue in the city of Chicago. Extracting data from CSV files, I analyzed statistics from Chicago public schools and Chicago parks to determine correlative relationships between the performance of students and the classifications of parks in areas surrounding the school. Studies show that children and students need co-curricular activities that take place outside the classroom, in order to develop and strengthen ‘soft’ skills, such as interpersonal communication, the acquisition of which has been shown to significantly increase the likelihood of future success. Inversely, in areas more prone to organized crime, parks can become a gathering place and lure students away from school to participate in illicit activities, thus proliferating crime.
Two files, Above_Average.txt and Far_Below_Average.txt, document the list of schools performing above average and far below average, respectively, as well as name and classification of parks that have the same zip code. The last lines of each file tally the number of types of each park.