Name: Attila Turkoz
Type: User
Company: DPA (State Of Colorado)
Bio: Developer. Data Analytics-Visualization (Uni of Denver)BC Cert.'19. ColoradoTech-MBA-Fin'14. Bogazici Uni Mech Eng'11. <Python, APEX, JS, VBA, M-Code, D3.js>
Location: Denver
Blog: https://attila5287.github.io/portfolio/
Attila Turkoz's Projects
angular js todo app
object oriented programming with APEX, playing card probability simulation
solutions for apexsandbox.io APEX practice questions total of 100 or so Apex 101, Database 101, Apex Language Features, SObjects, Lists, Sets, Maps and Data Structures & Algorithms.
github hosting
a python web app to be functioned as a freight management tracking tool for overseas automobile trade business
front end material for a freight tracking tool app to be used for shipping automobiles overseas
blackjack mobile friendly web app via python and flask framework module
ref files such as icons images txt csv etc to be uploaded here
blackjack monte-carlo simulation via python language and flask web framework module
Enjoy boilerplate repo for easy python flask webframework via heroku server. Aim is to provide an easy template, contribute if you could. by attila52
Bootstrap Color Extender adds several new colors to your already existing bootstrap website!
a Python web app dynamically updating Corona Virus COVID-19 data. d3 JS library for DOM, Plotly for charts, Flask for framework
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
Object Oriented Programming: Python module BeautifulSoup used to create a function that receives input from the user for item name and ad count then lists price-neighbourhood-title-link
Transform the DOM by selecting elements and joining to data.
one million four hundred thousand records of new york city. sent with job application screening assignment
python flask folium leaflet interactive maps
A free light weight jQuery plugin that allows you to create a custom drop down with images and description.
jQuery plugin to create a custom drop down with images and description.
displaytracker is a python -flask mobile friendly web app created to make inventory restocking easier for all users
displaytracker_img contains all images, icons etc designed or used in inventory tracking management web app displaytracker.herokuapp.com
database queries via Object Relational Mapper SQLalchemy + web framework editor Flask
introduction to big data analytics as well as pivot table/chart proficiency in Excel
VBA code creating a macro for big data analytics for abt 2M+rows in total
created per hw3 requirements
Code on a strong Python library for big data analytics: Pandas
A second code on a powerful data analytics library of Python: Pandas with education related data set
* You must use the Pandas Library and the Jupyter Notebook. * You must use the Matplotlib library. * You must include a written description of three observable trends based on the data. * You must use proper labeling of your plots, including aspects like: Plot Titles, Axes Labels, Legend Labels, X and Y Axis Limits, etc. * Your scatter plots must include [error bars](https://en.wikipedia.org/wiki/Error_bar). This will allow the company to account for variability between mice. You may want to look into [`pandas.DataFrame.sem`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.sem.html) for ideas on how to calculate this. * Remember when making your plots to consider aesthetics! * Your legends should not be overlaid on top of any data. * Your bar graph should indicate tumor growth as red and tumor reduction as green. It should also include a label with the percentage change for each bar. You may want to consult this [tutorial](http://composition.al/blog/2015/11/29/a-better-way-to-add-labels-to-bar-charts-with-matplotlib/) for relevant code snippets. * See [Starter Workbook](Pymaceuticals/pymaceuticals_starter.ipynb) for a reference on expected format. (Note: For this example, you are not required to match the tables or data frames included. Your only goal is to build the scatter plots and bar graphs. Consider the tables to be potential clues, but feel free to approach this problem, however, you like.) ## Hints and Considerations * Be warned: These are very challenging tasks. Be patient with yourself as you trudge through these problems. They will take time and there is no shame in fumbling along the way. Data visualization is equal parts exploration, equal parts resolution.