Source code for blog post: Interactive Data Visualization of Geospatial Data using D3.js, DC.js, Leaflet.js and Python
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Latest commit 2ee6da1 Aug 15, 2016 @adilmoujahid committed on GitHub Merge pull request #2 from mikejune/master
Fixed get_age_segment function typos.

README.md

Source Code for my blog post: Interactive Data Visualization of Geospatial Data using D3.js, DC.js, Leaflet.js and Python

Dependencies

You need Python 2.7.x and 3 Python libraries: Pandas, Flask, Shapely.

The easiest way to install Pandas is to install it as part of the Anaconda distribution.

You can install Flask and Shapely using pip.

pip install flask shapely

How to run the code

  1. Install all Python dependencies
  2. Download the dataset (gender_age_train.csv, events.csv, phone_brand_device_model.csv) from Kaggle. You need to create a Kaggle account and agree to the competition rules to download the data.
  3. Save the dataset in the input folder.
  4. From the root folder, run python app.py

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