Wooseom Cho Portfolio
As I delved deeper into my data analyst internship, I found myself fascinated by the power of data to inform decision-making and drive business growth, fueling my passion for data analytics and inspiring me to pursue it as a career.
I have developed a wide variety of skills from my previous Data Analytics roles and from classes I have taken as an Applied Mathematics major at Stony Brook University. Some of the courses I have taken was "Data Analysis". After taking a course in school, I realized that data analysis was a perfect fit for me and I became convinced that pursuing a career in this field was the right choice.
Covid-19 Death and Vaccination Data Exploration in SQL
A detailed analysis of COVID-19 data, encompassing case counts, death rates, and vaccination progress across global and regional scales. It delves into the proportion of population infected and the corresponding mortality, revealing patterns in infection and mortality rates across various locations. It focuses on vaccination data, calculating the percentage of population vaccinated in each location. A view is created for future data visualization, enabling an accessible understanding of the pandemic's progression.
Housing Data Cleaning in SQL
Involves cleaning and transforming a real estate dataset, specifically focused on properties in Nashville. The process includes standardizing date formats, populating missing property address data, and breaking down property and owner addresses into separate city, state, and address fields. The project also includes converting categorical values for better understanding and removing duplicate entries. Finally, unnecessary columns are dropped to streamline the dataset for further analysis.
Financial Transaction Data Exploration in SQL
Involves a detailed analysis of a financial transactions dataset. The initial phase involves checking for null values to ensure data quality. It then transitions into a comparative analysis of customer transactions, specifically focusing on different transaction methods (credit, debit, transfer) and their frequency of use by customers. Furthermore, it identifies the top 10 customers by total revenue and transaction frequency for each transaction method in the year 2022. Lastly, the project investigates instances of overlapping transaction_id and customer_id pairs, indicating potential duplicate entries in the dataset.
Electrical Vehicle Population Data Analysis and Visualization in Python
Focuses on the analysis of electric vehicle data with a special emphasis on Tesla models manufactured between 2020 and 2023. The analysis involves data filtering based on various attributes like the type of electric vehicle, electric range, and eligibility for Clean Alternative Fuel Vehicle (CAFV). The dataset is then manipulated and visualized to reveal insights such as the average electric range by make, and a choropleth map depicting the average electric range by state in the USA. The project aims to understand the distribution and performance of electric vehicles, particularly Tesla, across different parameters.
Myntra Online Shopping Data Exploration
The project involved an exploratory data analysis of a dataset containing information about products from the Myntra online shopping platform. Using Python and various data analysis libraries, I conducted data cleaning, visualization, and descriptive analysis to gain insights into product prices, ratings, sellers, and popularity. I loaded the dataset, removed irrelevant columns, and visualized correlations between variables. Additionally, I explored the distribution of prices, ratings, and total ratings, identifying top-rated products and popular sellers.