Name: Ken Kite
Type: User
Bio: Accomplished scientific programmer specializing in data engineering, visualization, & analysis. Stack includes Python, SQL, Java, JavaScript, VBA, HTML & CSS.
Location: St. Joseph, Michigan
Ken Kite's Projects
Mines spectrometry data from 4 tab delimited text files exported from a series of 4 blood analyzer units. From this data, calibration constants are calculated which are used to generate a barcode for the corresponding lot of sensors.
ETL kinetic data in the form of % transmittance and plots the 2nd derivative to monitor the behavior of the Lactate blood sensor being developed.
An automated backup tool to provide our customers free software to back up their instrument databases which typically exceed 1TB.
Python application I wrote for fun. I wanted to learn how to make a dash board using python 3, tkinter and matplotlib. I used csv files extracted from my bowling league website as the source data.
Mines spectrometry data from 24 csv files exported from a series of 3 electrolyte blood analyzer units. From this data, calibration constants are calculated which are applied to the corresponding lot of electrolyte sensors.
A website to provide a far more efficient mechanism of training our customers, than in a class room setting. The instrument software is highly complex and requires a strong background in chemistry to operate. It is unreasonable to expect customer to figure it out on their own.
Data Science Massive Open Online Course: All the code, notes and supplementary materials generated during the course of my data scientific learning.
Mines chromatographic data from 3,000 tab delimited text files exported from our Time of Flight Mass Spectrometer chemical analyzers and upload the relevant data to a SQL database. Then query and view the data by automatically dumping and plotting into an excel file.
ETL flat data exported from a Chemical Analyzer instrument (TOF-MS). While the data is still in memory, data is cleansed and linked so that primary and foreign keys can be generated prior to loading into a Postgres managed database using a Star schema. A CLI is implemented to query the DB to generate customizable data visualizations.
ETL the relevant data from thousands of tab delimited text files exported from our Time of Flight Mass Spectrometer chemical analyzers into an SQL database. The xlswriter python library is utilized to generate the data visualizations.
The first application wrote using python. Which is a game modeled after one of my childhood favorites called Dragon Warrior on NES.
Indroducing myself to the community.
It's been too many months since I've written any code and I'm getting antsy. The purpose of this repository is to keep my skills sharp.
This application is a tool designed to help our Service Department managers allocate their man hour resources more efficiently. It enabled projects to be better managed by accurately estimating timelines, proactively identifying deficiencies, and furthermore it successfully lobbied upper management to increase team head count.
Mines financial data from a *.csv file that I download from the financial institution which holds my mortgage. This tool provides valuable information relative to my financial planning.
Learning to use GitHub
Customers who purchased a service contract for their Time of Flight Mass Spectrometer received an annual Preventative Maintenance (PM) site visit. This automates tracking when a given customer was due for PM and what field service engineer was assigned the task based on their location.
ETL the user defined mass spectral data from ānā .*csv files exported from our Time of Flight Mass Spectrometer chemical analyzers. The data is listed in tables, plotted and basic statistics are calculated. This allows me to draw conclusions on the functionality of the instrument.
Extracts and cleanses flat data exported from a Chemical Analyzer instrument (Time of Flight Mass Spectrometer), then loads data into a SQL database using a Star schema. A basic CLI is implemented to query SQL database to create data visualizations which describe instrument performance in a simple and digestible manner. The following python libraries are utilized: numpy, pandas, matplotlib, sklearn, statistics, sqlite3, os, time, & datetime.
This application is a tool designed to help our Service Department managers allocate their man hour resources more efficiently. It enabled projects to be better managed by accurately estimating timelines, proactively identifying deficiencies, and furthermore it successfully lobbied upper management to increase team head count.
An upgrade to TimeTrax. It adds more powerful querying capabilities allowing the user to define the query conditions to output a scatter plot that visualizes the number of hours worked, on the user defined task per month, for the user defined employee(s).
Handy Stuff When I write VBA Macros in Excel