The goal of this project is to investigate a dataset of appoinment records for Brasil public hospitals. The data includes some attributes of patients and state if the patients showed up to appointments. The analysis should be focused on finding trends influencing patients to show or not show up to appointments. Using descriptive statistics the following question should be answered: What factors are important for us to know in order to predict if a patient will show up for their scheduled appointment? Predictive analytics is out of scope of this project.
The original problem description and data set can be found here: https://www.kaggle.com/joniarroba/noshowappointments/home
This project was completed as part of Udacity's Data Analyst Nanodegree certification.
I have looked into the dataset and managed a few problems like unifying names, removing wrong data, adding new features based on existing data. I have also investigated most of independent variables in the dataset and made a few observations comparing them to each other as well as to the dependent one (no_show). As this was only an exploratory analysis, many potential correlations may remain uncovered. The data should be investigated further with more advanced statistical analysis to potentially reveal new insights and correlations.