Data analytics in Python a functional approach
An elementary data science project to mark my first entry in the field.
Abstract - Methods used for data analysis considering a data set of 311 calls in NYC for non-emergency government services and information. Python and SQL are applied to conduct statistical analysis using functional and declarative approaches respectively considering performance, ease of use and readability. Hypotheses are drawn to direct the analysis toward meaningful conclusions and correlations, causation’s are considered within the data context.
Conclusion - In the context of this data set the hypothesis H1 was correct that calls increased during March compared to August. Further analysis is necessary to draw a complete conclusion and correlations. Employing a more object-orientated approach would be beneficial for recovery and other improvement aspects. Optimization is necessary for faster computation using pandas. Since the data is unordered, ordering the data by UIN or date would be the next step for a stronger analysis.