No-show Appointments

Data Science I, Foundation Nanodegree Program Udacity - Final Project Submission (Investigate a Dataset: No-show appointments)

This project consisted to analyze a dataset and then communicate findings about it. Was use Python libraries like NumPy, Pandas, Matplotlib, Seaborn, Io and Requests.

This dataset collects information from 100k medical appointments in Brazil and is focused on the question of whether or not patients show up for their appointment. A number of characteristics about the patient are included in each row.

Dataset URL: https://d17h27t6h515a5.cloudfront.net/topher/2017/October/59dd2e9a_noshowappointments-kagglev2-may-2016/noshowappointments-kagglev2-may-2016.csv

Data Dictionary:

• PatientId - Identification of a patient;
• AppointmentID - Identification of each appointment;
• Gender = Male or Female . Female is the greater proportion, woman takes way more care of they health in comparison to man;
• AppointmentDay = The day of the actuall appointment, when they have to visit the doctor;
• ScheduledDay = The day someone called or registered the appointment, this is before appointment of course;
• Age = How old is the patient;
• Neighbourhood = Where the appointment takes place;
• Scholarship = Ture of False . Observation, this is a broad topic, consider reading this article https://en.wikipedia.org/wiki/Bolsa_Fam%C3%ADlia;
• Hipertension = True or False;
• Diabetes = True or False;
• Alcoholism = True or False;
• Handcap = True or False;
• SMS_received = 1 or more messages sent to the patient;
• No-show = True or False.