Early stage Diabetes risk prediction data analysis

In this project i tried to map the relation between patient's early symptoms and their chances of getting diabetes. I have also found out the combination of symptoms which were crucial in early stage detection of diabetes.

This project is free from any plagiarism and is my genuine work.(Upendra Kumar Jena)

Dataset Information:
I foun this dataset from 'UCl Machine Learning Repository'(http://archive.ics.uci.edu/ml/datasets/Early+stage+diabetes+risk+prediction+dataset.) in Newest dataset collections.

This has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor.

Attribute Information:
Age 1.20-65 Sex 1. Male, 2.Female Polyuria 1.Yes, 2.No. Polydipsia 1.Yes, 2.No. sudden weight loss 1.Yes, 2.No. weakness 1.Yes, 2.No. Polyphagia 1.Yes, 2.No. Genital thrush 1.Yes, 2.No. visual blurring 1.Yes, 2.No. Itching 1.Yes, 2.No. Irritability 1.Yes, 2.No. delayed healing 1.Yes, 2.No. partial paresis 1.Yes, 2.No. muscle stiffness 1.Yes, 2.No. Alopecia 1.Yes, 2.No. Obesity 1.Yes, 2.No. Class 1.Positive, 2.Negative.

About Course:
This project work is for partial fulfillment of an online certification course 'Zero to Pandas'the course which was provided by Jovian.ml. This course covered from basic concepts of python and Numpy and moved towards data analysis with Pandas and plotting tools like matplotlib and Seaborn and steps to use these knowledge to analyse a real world data. The video lectures were very nice and specific towards course objectives. The instructor's presentations were neat and beautiful with smooth transition of topics. Infact this is one of the best online courses i have come across in terms of course objectives fulfillment, it helped me a lot to build up my basic foundation on data analysis. Thanks to Aakash N S and team Jovian and freecodecamp.org for all these.

Let's begin by downloading the data, and listing the files within the dataset.