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aperconti committed Nov 6, 2020
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Expand Up @@ -127,38 +127,39 @@ <h3 class="text-center serif">Projects</h3>
<a href="https://github.com/aperconti/python-api-challenge" target="_blank"> <strong> Weather Data
Analysis </strong> </a>
<br>
Created a Python script to visualize the weather of 500+ cities across the world of varying distance
from the equator.
This project utilized the Python library, the OpenWeatherMap API. I am the sole contributor to this
In this project, I created a Python script to visualize the weather of 500+ cities across the world
of varying distances
from the equator. This project utilized the Python library and the OpenWeatherMap API. I am the sole
contributor to this
project.
<br>
<br>
<br>
<a href="https://github.com/aperconti/python-challenge" target="_blank"> <strong> Data Analysis in
Python </strong> </a>
<br>
<strong>Part A: </strong>Created a Python script for analyzing the financial records from a dataset.
I am the sole
contributor to this
project.
<a href="https://github.com/aperconti/javascript-challenge" target="_blank"> <strong> SQLAlchemy
flask app
</strong> </a>
<br>
<strong>Part B: </strong>Created a python script for analyzing/calculating the voting results from a
dataset. I am
the sole contributor
to this project.
This project used SQLAlchemy create_engine to connect to my sqlite database in a jupyter notebook.
The cleaned data is
made visible in the Flask app and interactable with the user able to visualize weather data for the
vacation days
selected. I am the sole contributor to this repo.
<br>
<br>
<br>
<a href="https://github.com/aperconti/sqlalchemy-challenge" target="_blank"> <strong> SQLalchemy
<a href="https://github.com/aperconti/Endangered-Species" target="_blank"> <strong> ETLV
</strong>
</a>
<br>
This project used Python and SQLAlchemy to conduct basic climate analysis and data exploration in a
SQL database. This
portion of the project was completed using SQLAlchemy ORM queries, Pandas, and Matplotlib.
After completing the initial analysis, a Flask API was implemented based on the queries completed in
part one of the
project.
This project used python to extract and transform the data before being loaded into MongoDB. The
visualizations were
created with Leaflet and viewed through a flask app.
The purpose of this project was to visualize the correlations between population density and
endangered birds and
plants. As a group project, I contributed the data extraction, cleaning, loading into the database,
bootstrap webpage,
leaflet map layers, and jquery navbar.

<br>
<br>
</p>
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