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https://github.com/melvinjwallace/portfolioprojects


https://github.com/melvinjwallace/portfolioprojects

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# Melvin J Wallace Portfolio Projects



# US Regional Sales Project



## Introduction



This is a python project that I completed on the **US Regional Sales** dataset. The aim in the project is to analyze and derive insights to answer

critical questions that can help stakeholders make the best data driven decisions.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and does not represent any real company. It is being used simply for the purposes 

of demonstratinig my data analysis capabilities and the capabilities of Python and a few of its libraries._



## Problem Statement

1. What products sold the most by year, month, and day?

2. Which sales team member sold the most?

3. Average unit price sold by each sales team member?

4. Number of orders sold by sales channel?

5. Minimum, Average, and Maximum order price per customer?

6. Whats the average markup or profit per unit?

7. Whats the average markup or profit per unit by year and month?



## Skills Demonstrated:

- Importing libraries

- Reading data

- Data cleaning,

- Data manipulation

- Data processing

- Data visualizations.



# Middle East Conflict Project



## Introduction



This is a python project that I found intresting and completed on the **Fatalaties of Israelies and Palestinians Conflict from 2000 to 2023**. 

My goal in this project was to analyze and intrepet the data to let it tell its own story.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and is open source. I am in no way supporting violence on either side of 

the trajic events that have taken place over two decades during this conflict and my heart goes out to everyone experiencing loss and grief._ 



## Problem Statements

1. What was the age of the oldest, and youngest victim?

2. What is the average age of a victim?

3. Number of victims by citizenship?

4. Youngest and oldest victims by citizenship?

5. Average age of victims by citizenship and gender?

6. Oldest and youngest victims by citizenship and gender?

7. Number of victims by region and gender?

8. Number of victims by gender and type of injury?

9. Number of groups that killed the most victims by region?

10. Most common injury types?

11. Number of injury types by gender?

12. Years with highest number of victims?

13. Number of victims by month?

14. Number of victims by gender per month?

15. Number of victims by gender and citizenship per day?



## Skills Demonstrated:

- Importing libraries

- Reading in data to dataframe

- Cleaning data

- Data manipulation

- Data visualization



# Chicago Crime Project



## Introduction



This is a python project that I found on **Chicago Crimes from 2001-2023**. This dataset is particularly close to me as I am a 

resident of Chicago. My goal in this project is to analyze the different crimes by district, year, and month, searching for trends 

that can potentially lead to helping reduce overall crime in the city of Chicago.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and is open source. The data is being used for a personal project

for the purposes of identifying trends in relation to the crime rate in the city of Chicago_.



## Problem Statements

1. What are the top 10 crimes?

2. Most case by year?

3. Number of crimes that resulted in arrest?

4. Number of crimes that resulted in non-arrest?

5. Percentage of arrest vs non-arrest crimes?

6. Count of crime type by year?

7. Count of crime type by year that resulted in arrest?

8. Count of crime type by year that resulted in non-arrest?

9. Most crimes by year?

10. Most crimes by day and month?

11. Number of crimes by month resulting in arrest and non-arrest?

12. Most crimes by district?



## Skills Demonstrated

- Importing Libraries 

- Reading in data to dataframe

- Data cleaning

- Manipulating data

- Data transformation

- Data processing

- Data visualizations



# Texas Deathrow Project



## Introduction



This is a mssql server project that I completed on **Texas Deathrow Inmates**.  My goal in this project was to demonstrate my data cleaning, data transformation, data manipulation and exploratory data analysis capabilities using sql.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and the data begins in 1976, the year the death penalty was reinstated, to present. This data is open source and is being used for a personal project_.



## Problem Statements

1. How many inmates have there been by race?

2. Whats the lowest, average, and highest educational level of all inmates?

3. Whats the minimum, average, and maximum age of all inmates executed?

4. Whats the minimum, average, and maximum age of all inmates executed with the average education?

5. Number of different races executed with average educational level?

6. Percent of different races executed with average educational level?

7. Number of different eye colors for inmates with an average educational level?

8. Whats the minimum, average, maximum weight of inmates by race with an average educational level?

9. Whats the minimum, average, and maximum birth year?

10. Whats the minimum, average, and maximum birth year by race with an average educational level?

11. Whats the minimum, average, and maximum execution year for all inmates?

12. Most amount of years spent on deathrow before execution by race?

13. Most amount of years spent on deathrow before execution by race with an average educational level?

14. Least amount of years spent on deathrow before execution by race?

15. Average amount of years spent on deathrow before execution by race?

16. How many apologetic last statements were spoken by race?



## Skills Demonstrated

- Data manipulation 

- Data cleaning 

- Data processing percentage values from numerical data)

- Exploratory data analysis



# Video Game Sales



## Introduction



This is a python project that I completed on **Video Game Sales as of Dec 2016**. I found this dataset intresting because as a kid, I grew up playing video games on many different consoles. My goal in this project was to see what was the most popular game, and console around the globe.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and is open source data. The data begins in the year 1985 and ends in the year 2016_.



## Problem Statements

1. What are the top 10 games across all platforms?

2. What are the top 10 platforms?

3. What are the top 10 platforms by year?

4. What are the top 10 release years by North American sales?

5. What are the top 10 release years by European sales?

6. What are the top 10 release years by Japan sales?

7. What are the top 10 platforms by year of release golobal sales?

8. What are the total sales for all regions?

9. What is the percentage of total sales by all regions?



## Skills Demonstrated

- Importing libraries

- Data cleaning

- Data manipulation

- Data processing

- EDA

- Data visualizatioin



# Student Performance Project



## Introduction



This is a python project that I completed on **Student Performance**. The purpose of this project was to see if there were any correlations between any of the variables that contribute to higher or lower scores from the students. This was achieved by grouping different variables and performing various aggregations to find insights.



**_Disclaimer_**: _This dataset was retrieved from the Kaggle website and is open source data. The data is completely fictional and is not a representation of any particular person or group of people_.



## Problem Statements

1. How many students are there by gender?

2. How many students are there by race/ethnicity?

3. What is the percentage of students by race/ethnicity?

4. How many students are there by gender and by race/ethnicity?

5. What is the count of the parents educational level by all students?

6. What is the count of the parents educational level by gender?

7. What is the count of the parents educational level by race/ethnicity?

8. What is the number of students by lunch type?

9. What is the number of students by gender and lunch type?

10. What is the number of students by test preparation?

11. What is the number of students by gender and test preparation?

12. What is the average, maximum, and minimum math, reading, and writing scores by gender and test preparation?

13. What is the average, maximum, and minimum math, reading, and writing scores by gender and race/ethnicity?



## Skills Demonstrated

- Importing libraries

- Data cleaning

- Data manipulation

- Data processing

- Exploratory data analysis

- Data visualizations



# Healthcare Project



## Introduction



This is a personal project that I completed on a **Healthcare** dataset utilizing the power of python. The purpose of this project was to demonstrate my understanding and knowledge of the data analysis process and to provide insights from the data. I achieved that by manipulating the data, transforming the data, processing the data, and then rpoviding visualizations the data.



**_Disclaimer_**: _This dataset is completly made up of fictional characters. The dataset was retrieved from the Kaggle website and is open source_. 



## Problem Statements

1. What is the average age of male and female patients?

2. What is the count of blood types by gender?

3. What is the count of medical conditions?

4. What is the count of medical conditions by gender?

5. How many patients are there per insurance provider?

6. How many patients are there per insurance provider by gender?

7. How many patients are there per admissioin type?

8. How many patients are there by gender per admission type?

9. How many patients are there per test results?

10. How many patients are there by gender per test results?

11. What is the number of patients per medication?

12. How many patients are there by admission year/month/day?

13. What is the minimum/average/maximum billing amounts by gender?

14. What are the minimum/average/maximum billing amounts by medical condition?

15. What are the minimum/average/maximum billing amounts by insurance provider?

16. What are the billing amounts by admission type?

17. What are the billing amounts by medication and gender?

18. What are the average billing amounts by admission year/month/day?



## Skills Demonstrated

- Importing libraries

- Retrieving/Reading data to dataframe

- Data manipulation

- Data cleaning

- Data processing

- Exploratory data analysis

- Data visualization