Stack Overflow Developer Survey Analysis

Project Overview

This project analyzes data from the 2017 Stack Overflow Developer Survey to uncover insights about developer demographics, job satisfaction, work environments, and salary trends. By examining factors such as company type, years of experience, remote work preferences, and compensation, this analysis provides a deeper understanding of developer experiences and industry patterns.

Dataset

• Data Files:

  • survey_results_public.csv: Contains individual responses to the Stack Overflow survey.
  • survey_results_schema.csv: Describes each column in the survey responses.

• Key Variables:

  • CompanyType: Type of company employing the developer.
  • YearsProgram: Years of programming experience.
  • JobSatisfaction: Self-reported job satisfaction level.
  • HomeRemote: Preference for remote work.
  • Salary: Self-reported annual salary.

• Source: Stack Overflow Developer Survey 2017.

Project Structure

1. Data Understanding:

   • Load and inspect the datasets for an initial overview.
   • Display column names, data types, and basic statistics.

2. Data Cleaning:

   • Handle missing values in key columns, particularly those relevant to company type, years of experience, job satisfaction, and salary.
   • Apply transformations to clean and prepare the data for analysis.

3. Exploratory Data Analysis (EDA):

   • Explore key relationships and patterns in the data:
     • Distribution of job satisfaction and salary.
     • Correlation between years of experience and compensation.
     • Analysis of remote vs. in-office work preferences.

4. Visualizations:

   • Generate visualizations to represent the data:
     • Salary distribution across different experience levels.
     • Job satisfaction levels by company type.
     • Developer preferences for remote work.

Technologies Used

• Programming Language: Python
• Libraries: Pandas for data manipulation, Matplotlib and Seaborn for visualization.

Insights & Key Findings

• Analysis of job satisfaction across company types and experience levels.
• Salary distribution patterns based on experience and other factors.
• Trends in remote work preferences among developers.

Future Work

I am working on a few advanced visualizations (heatmap etc)

Usage

1. Clone the repository.
2. Install necessary Python libraries:

   pip install pandas matplotlib seaborn