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Source for blog post: Interactive Data Visualization with D3.js, DC.js, Python, and MongoDB

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@oserikov: in this fork I naively removed the necessity to use Mongo. As the dataset is not that big actually, pandas serves fine, yet even pandas can be dropped, as we only read the whole csv into a list of dicts. The data itself is part of a larger project, and turns out to be hosted on Kaggle novadays. Notice that you have to merge two csv's to get the desired one: projects.csv and donations.csv. Find the merged lightweight file here in this repo.

DonorsChoose_Visualization

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Getting started

The dependencies for the project can be installed using $ pip install -r requirements.txt
the only dependencies needed are pandas and flask

You can use Vagrant to start a machine with a MongoDB instance running vagrant up To initialize the database you need to download the data $ wget https://s3.amazonaws.com/open_data/csv/opendata_projects.zip && unzip opendata_projects.zip and import it $ mongoimport -d donorschoose -c projects --type csv --file /vagrant/opendata_projects.csv -headerline
Mongo is not needed anymore

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Source for blog post: Interactive Data Visualization with D3.js, DC.js, Python, and MongoDB

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