SQL E-Commerce Analysis
Website traffic and performance data to quantify the company's growth
SQL E-Commerce Analysis
DATA CLEANING IN SQL
Converting Data type, Finding missing values using SELF JOIN, Breaking out Address into Individual Columns (Address, City, State) using SUBSTRING AND CHARINDEX, Split OwnerAddress using PARSENAME and REPLACE, Change Y and N to Yes and No in “Sold as Vacant” field using CASE WHEN statement, Remove Duplicates using CTE, and delete unused columns
Python Logistic Regression
Explore data using Seaborn visualization. Clean data by filling in or droping missing vales. Convert categorical features with dummies variables. Use Logistic Regression to predict survival rate.
Python 911 call Analysis
Clean and Analyze 911 calls from Kaggle data source, using pandas, numpy, matplotlib, seaborn, using groupby(), apply(), map(), lambda function. Data was analyzed using seaborn and matplotlib visualization.
UK Bank Customers
interactive Tableau Dashboard
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Created this dashboard using Table calculation, parameters to adjust the size of the bins, Filter function to make the dashboard interactive, created storytelling line.
Data Exploration in SQL
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Data representing then number of confirmed deaths from COVID-19 across the world, sbefore and after vaccinations
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