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Best-Brain-Gang / Crowdfunding_Analysis

This project attempts to help project creators understand how to market their project on Kickstarter vs Indiegogo. The purpose of this tool is to not only give them advice on platforms but be able to efficiently market their project and provide supporting data for whichever is the better platform.
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Research a new Python library not previously covered in the course. #15

Closed juzcho closed 3 years ago

juzcho commented 3 years ago

Major Requirement for the Project.

juzcho commented 3 years ago

folium: https://python-visualization.github.io/folium/quickstart.html

Narwhilian commented 3 years ago

The stats models library seems like it has a lot of potential to me. here is the link with the write up and functions, not all of them would be applicable seeing as we arent doing something time series related but some of them look pretty promising to me

https://www.statsmodels.org/stable/index.html

n8patterson commented 3 years ago

This is related to #9, so closing #9 in favor of this.

https://mode.com/blog/python-data-visualization-libraries/

n8patterson commented 3 years ago

If you guys want to use the small kickstarter datasets. I will need to use the fixer.io API to convert the money cols to USD based to match our other dfs. So I will import and use a fixer.io package with:

pip install fixerio

easy_install fixerio

from fixerio import Fixerio

Link for reference:

https://fixerio.readthedocs.io/en/latest/ https://fixer.io/documentation

n8patterson commented 3 years ago

Papermill to seperate code: https://papermill.readthedocs.io/en/latest/usage-execute.html

n8patterson commented 3 years ago

Ended up not using fixer.io. It does not really make sense to use on the small kickstarter data because we don't have any launched or deadline dates.

n8patterson commented 3 years ago

Adding viz libs to close this issue. Here is a link of what I added. https://towardsdatascience.com/top-6-python-libraries-for-visualization-which-one-to-use-fe43381cd658

Each graphs different things better. Look at the related sites to see which one you want to use. We can remove whatever we don't use later.

For each do the following to your dev env. @cdhendy @juzcho We should add the below to the readme later.

Seaborn: conda install seaborn Altair: conda install -c conda-forge altair Bokeh: conda install bokeh Folium: conda install folium -c conda-forge