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Attila Turkoz's Projects

apex-sandbox-io icon apex-sandbox-io

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.

berenice icon berenice

a python web app to be functioned as a freight management tracking tool for overseas automobile trade business

berenice_img icon berenice_img

front end material for a freight tracking tool app to be used for shipping automobiles overseas

blackjack_app icon blackjack_app

blackjack mobile friendly web app via python and flask framework module

blueprints_heroku_boilerplate icon blueprints_heroku_boilerplate

Enjoy boilerplate repo for easy python flask webframework via heroku server. Aim is to provide an easy template, contribute if you could. by attila52

coronavizdata icon coronavizdata

a Python web app dynamically updating Corona Virus COVID-19 data. d3 JS library for DOM, Plotly for charts, Flask for framework

covid-19 icon covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

craigslist_mania_beautifulsoup_mongodb icon craigslist_mania_beautifulsoup_mongodb

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

d3-selection icon d3-selection

Transform the DOM by selecting elements and joining to data.

ddslick icon ddslick

A free light weight jQuery plugin that allows you to create a custom drop down with images and description.

ddslick-1 icon ddslick-1

jQuery plugin to create a custom drop down with images and description.

displaytracker icon displaytracker

displaytracker is a python -flask mobile friendly web app created to make inventory restocking easier for all users

displaytracker_img icon displaytracker_img

displaytracker_img contains all images, icons etc designed or used in inventory tracking management web app displaytracker.herokuapp.com

du_bigdata_hw5_matplotlib-pyber icon du_bigdata_hw5_matplotlib-pyber

* 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.

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