This project is the Blog Post for the Data Scientist Nanodegree Program from Udacity. I choose to work on a Diabetes Dataset from Kaggle website. This data set contains several medical predictor (independent) variables and one target (dependent) variable, Outcome. Independent variables include the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.
- Pandas Library; Pandas is a software library written for the Python programming language for data manipulation and analysis.
- Numpy Library; NumPy is a Python library used for working with arrays.NumPy stands for Numerical Python.
- Matplotlib Library; Matplotlib is a cross-platform, data visualization and graphical plotting library for Python and its numerical extension NumPy.
- Seaborn Library ; Seaborn is an open-source Python library built on top of matplotlib. It is used for data visualization and exploratory data analysis.
- Plotly.express Library; Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.
It sets the backend of matplotlib to the 'inline' backend: With this backend, the output of plotting commands is displayed inline within frontends like the Jupyter notebook, directly below the code cell that produced it.
My motivation was about answering questions related to the Diabetes. I found my answers in this dataset using python packages pandas , numpy , seaborn , matplotlib ,plotly.express My questions was about the following: How many people have diabetes? How many women are affected by diabetes during pregnancy? What is the average of Glucose for the people who are affected by diabetes?
- README.md: Short Brief about the project goal, used libraries and the results.
- Diabetes -Project 1.ipynb the code waswrittin by pythin 3 using jypter notbook
- Diabetes.csv the file contains the dataset from Kaggle.
After answering three questions we can said , the people who are affected by diabetes is less than who are not. The percentage for the women who are affected by diabetes during pregnancy which is (44.2%).In addition the average of Glucose for the people who are affected by diabetes is 141.26 which is greater than the people who are not affected by diabetes.
https://medium.com/@bashayer/project-data-science-blog-post-diabetes-dataset-b93919e6bbf4
Following are the features provided in the dataset.
- Pregnancies = No. of pregnancy
- Glucose = Glucose level
- Blood Pressure = Plood Pressure of person
- SkinThickness = Thickness of the skin
- Insulin = Insulin Test results
- BMI = Body Mass Index
- Diabetes Pedigree Function
- Age = Age of the person
- Outcome = Target class (wether diabetes or not, 1: diabetec, 0: not diabeteic)