Data-Science-Salary-Analysis

Python programs and technical report on data understanding, preparation, exploration, and initial analysis

Data Set Description

The data contains the information about various factors which can influence salary levels such as experience, work level, job title and many more. The objective of this analysis is to obtain a better understanding of the elements that influence the salaries of data scientists and discover any regularities or tendencies within the data.

Data Analysis Steps

1. Data Understanding:

   • Explore the dataset to understand its structure, variables, and data types.
   • Identify any missing values or outliers that need to be addressed.

2. Data Preparation:

   • Clean the data by handling missing values, outliers, and inconsistencies.
   • Perform data transformations, such as scaling or encoding categorical variables.

3. Data Exploration:

   • Analyze the relationships between variables using statistical measures and visualizations.
   • Identify patterns, trends, and correlations in the data.