Data-Visualizations-of-employee-productivity-and-landscaping-job-completion-times

it is a comprehensive collection of data analysis and visualizations. It cover a wide range of scenarios, from exploring employee productivity and landscaping job completion times to assessing the overall productivity of a business.

Python Data Analysis and Visualizations

Welcome to the Python-Data-Analysis-Visualizations repository! This collection of Python code snippets showcases various scenarios related to data analysis and visualizations. Below are instructions for running and exploring the provided snippets.

Instructions

1. Employee Productivity Scatterplot

• Navigate to the "employee_productivity_scatterplot" directory.
• Run the Python script using your preferred Python interpreter.
• Explore the scatterplot showing the relationship between employee hourly wage and productivity.

2. Landscaping Job Completion Time Analysis

• Navigate to the "job_completion_time_analysis" directory.
• Run the Python script using your preferred Python interpreter.
• Explore the bar chart depicting job completion time by job type.
• Check the additional snippet for a bar chart of time spent on different landscaping tasks.

3. Business Overall Productivity Analysis

• Navigate to the "business_overall_productivity_analysis" directory.
• Run the Python script using your preferred Python interpreter.
• Explore the heatmap illustrating the correlation matrix between different factors and productivity.
• Check the snippets for visualizing the relationship between job type, customer satisfaction, and material costs with productivity.

Requirements

Ensure you have the required Python libraries installed. You can install them using the following command:

pip install pandas matplotlib seaborn