Used data analytics and visualization to draw valuable insights for the patients no-show scenarios

A medical appointments data set is used, which consists of patient's details (nearly 100k) and their presence based on the schedule

Data set can be downloaded here: https://www.kaggle.com/datasets/marwandiab/medical-appointment-no-shows-dataset

Libraries used: numpy, pandas, seaborn, matplolib (all are in-built with jupyter notebook)

Analysed the dataset to estimate the factors that affect patients to miss their appointment. Following factors/columns are considered:

1. gender
2. age
3. time difference between schedule and appointment
4. sms sent/not sent
5. scholarship
6. neighbourhood

Processes involved:

1. Data wrangling
2. Data cleaning
3. Data analysis

While many conclusions were drawn from the above factors, yet data can be improved detailed to enhance detailed analytics.