V-MalM
Extensive hands-on experience in developing optimized database functionalities to improve data storage, retrieval, and workflow efficiencies.
Software Engineer / Data AnalystSt Louis Area
Pinned Repositories
Analysis-Using-PostgreSQL
Design Postgresql tables, import the CSVs into the database, and answer questions about the data.
Analysis-Using-Python
Read an individual csv file, analyze data, perform calculations, print summary of analysis to screen and also create an output text file and write summary of analysis to it.
Climate-analysis
Basic Climate analysis and data exploration of climate database. The analysis was completed by using SQLAlchemy ORM queries, Pandas, and Matplotlib
Cryptocurrency-Clusters
To create a report that includes what cryptocurrencies are on the trading market and determine whether they can be grouped to create a classification system for this new investment.
ETL
A Case Study of Extract, Transform, Load. Documentaion includes sources of data, types of data wrangling performed (data cleaning, joining, filtering, and aggregating) and the schemata used in the final production database. Technologies used include Pandas, PostgreSQL, Jupyter Notebook.
Hazardous-air-pollutants-in-CA
Analyze the Hazardous Air Pollutant data for the State of CA from 1990 to 2017 and produce informative conclusions about the causes and effects of air pollution. Technologies Used: Pandas, Matplotlib, Jupyter Notebook
MAZE
Analyzing the data for nation's Museums, Zoos, Aquariums, and Nature Centers and creating an interactive dashboard to help users to plan trips, help with career choices if interested in museums and, historic preservation. Technologies Used: Javascript, PostgreSQL, Python, Flask, Leaflet, Plotly, HTML/CSS, Bootstrap, JQuery.
Plotly_B3
An interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels.
PlotPower-Matplotlib
Data analysis on the potential treatments for Squamous Cell Carcinoma (SCC), a common variant of skin cancer.
Stock-Clustering-and-Prediction
To build, train and test LSTM model to forecast next day 'Close' price and to create diverse stock portfolios using k-means clustering to detect patterns in stocks that move similarly with an underlying trend i.e., for a given period, how stocks trend together.To deploy our findings to an app along with an interactive dashboard to predict the next day ‘Close’ for any given stock.
V-MalM's Repositories
V-MalM/ETL
A Case Study of Extract, Transform, Load. Documentaion includes sources of data, types of data wrangling performed (data cleaning, joining, filtering, and aggregating) and the schemata used in the final production database. Technologies used include Pandas, PostgreSQL, Jupyter Notebook.
V-MalM/Stock-Clustering-and-Prediction
To build, train and test LSTM model to forecast next day 'Close' price and to create diverse stock portfolios using k-means clustering to detect patterns in stocks that move similarly with an underlying trend i.e., for a given period, how stocks trend together.To deploy our findings to an app along with an interactive dashboard to predict the next day ‘Close’ for any given stock.
V-MalM/Analysis-Using-PostgreSQL
Design Postgresql tables, import the CSVs into the database, and answer questions about the data.
V-MalM/Analysis-Using-Python
Read an individual csv file, analyze data, perform calculations, print summary of analysis to screen and also create an output text file and write summary of analysis to it.
V-MalM/Climate-analysis
Basic Climate analysis and data exploration of climate database. The analysis was completed by using SQLAlchemy ORM queries, Pandas, and Matplotlib
V-MalM/Cryptocurrency-Clusters
To create a report that includes what cryptocurrencies are on the trading market and determine whether they can be grouped to create a classification system for this new investment.
V-MalM/Hazardous-air-pollutants-in-CA
Analyze the Hazardous Air Pollutant data for the State of CA from 1990 to 2017 and produce informative conclusions about the causes and effects of air pollution. Technologies Used: Pandas, Matplotlib, Jupyter Notebook
V-MalM/MAZE
Analyzing the data for nation's Museums, Zoos, Aquariums, and Nature Centers and creating an interactive dashboard to help users to plan trips, help with career choices if interested in museums and, historic preservation. Technologies Used: Javascript, PostgreSQL, Python, Flask, Leaflet, Plotly, HTML/CSS, Bootstrap, JQuery.
V-MalM/Plotly_B3
An interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels.
V-MalM/PlotPower-Matplotlib
Data analysis on the potential treatments for Squamous Cell Carcinoma (SCC), a common variant of skin cancer.
V-MalM/Predicting-Credit-Risk-Supervised-ML
A supervised machine learning model that attempts to predict whether a loan from LendingClub will become high risk or not.
V-MalM/Report-Using-Pandas
Generate a report for an independent gaming company by analyzing the data for their most recent fantasy game Heroes of Pymoli that breaks down the game's purchasing data into meaningful insights.
V-MalM/stock-market-data-analysis
VBA Excel macro that reads excel workbook containing stock data, (each worksheet containing one year's data) and outputs required information.
V-MalM/Visualizing-Data-with-Leaflet
This app uses earthquake data from USGS and visualizations are created by plotting it on the map using Leaflet.
V-MalM/web-scraping
Web application to scrape various websites for data related to the Mission to Mars and displays the information in a single HTML page.
V-MalM/What-s-the-weather-like
Created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator by utilizing Python library - citipy, and the OpenWeatherMap API, to create a representative model of weather across world cities.
V-MalM/World-Weather-Web-Visualization
Web design with Bootstrap. To visualize the weather of 500+ cities across the world of varying distance from the equator by utilizing Python library - citipy, and the OpenWeatherMap API and to create a representative model of weather across world cities.