MeriSkill Diabetes Prediction Project

Project Tasks:

Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.

From the data set in the (.csv) File We can find several variables, some of them are independent
(several medical predictor variables) and only one target dependent variable (Outcome).

Other Important Task in this project are:

Data Cleaning:

• Delete Redundant Columns:

  • I removed redundant columns to streamline the dataset.

• Rename Columns:

  • I ensured clear and descriptive column names for better understanding.

• Drop Duplicates:

  • I eliminated duplicate entries to maintain data accuracy.

• Clean Individual Columns:

  • I performed specific cleaning tasks on columns as needed.

• Remove NaN Values:

  • I addressed missing data by removing NaN values from the dataset.

• Additional Transformations:

  • I conducted further transformations to enhance data usability.

Data Visualization:

• Visualizations on Demographic information

  • I created a dashboard displaying the demographic information.

• Visualizations on Various Variables:

  • I created visualizations for Overtime, Marital Status, Job Role, Gender, Education Field, Department, and Business Travel.

• Relations Between Variables:

  • I explored and visualized relationships between Overtime and Age, Total Working Years, Education Level, Number of Companies Worked, and Distance from Home.