This repo is developed by Emanuel Fontelles.
Some notebooks to understand how to use Plot.ly and geopandas
This project aim to demonstrate you some Python visualizitions tools, some libraries as Plotly and Geopandas are enphasyses because of its facilities
Many excellent plotting libraries exist in Python, including the main ones:
- Starting with Plot.ly
- Choropleth Graphs
- Create choropleth from csv e pandas
- Geospatial Data Analysis, Geojsonio and Geopandas
- Geopandas from documentation
- Creating a GeoDataFrame from a DataFrame
- Kernel Density Estimation
You can view the tutorial materials using the excellent service from Binder. Click in the Binder bagde to play with the notebooks from your browser without installing anything or you can setup a local instalation.
Binder lets you easily host interactive Jupyter notebooks and let anyone on the internet use them interactively immediately! Binder creates executable environment making your code immediately reproducible by anyone, anywhere.
You can visualize the notebooks without running any kernel.
This tutorial requires the following packages:
- Python version 2.7 or 3.6+
numpy
version 1.15 or later: http://www.numpy.org/scipy
version 0.10 or later: http://www.scipy.org/matplotlib
version 2.2.2 or later: http://matplotlib.org/scikit-learn
version 0.19.2 or later: http://scikit-learn.orgipython
version 2.0 or later, with notebook support: http://ipython.orgseaborn
version 0.8 or later: https://seaborn.pydata.org/plotly
version 3.3.1 or later: https://plot.ly/
For a local installation, please follow the tutorial bellow. If you don't know how to install those on your platform, I recommend to install Miniconda, a distribution of the conda package and environment manager. Please follow the below instructions to install it and create an environment for the repository.
- Download the Python 3.x installer for Windows, macOS, or Linux from
https://conda.io/miniconda.html and install with default settings. Skip
this step if you have conda already installed (from Miniconda or
Anaconda). Linux users may prefer to use their package manager.
- Windows: Double-click on the
.exe
file. - macOS: Run
bash Miniconda3-latest-MacOSX-x86_64.sh
in your terminal. - Linux: Run
bash Miniconda3-latest-Linux-x86_64.sh
in your terminal.
- Windows: Double-click on the
- Open a terminal. Windows: open the Anaconda Prompt from the Start menu.
Once this is installed, the following command will install all required packages in your Python environment:
$ conda install numpy scipy matplotlib scikit-learn ipython-notebook seaborn
Alternatively, you can download and install the (very large) Anaconda software distribution.
Every time you want to work, do the following:
- Open a terminal. Windows: open the Anaconda Prompt from the Start menu.
- Start Jupyter with
jupyter notebook
orjupyter lab
. The command should open a new tab in your web browser. - Edit and run the notebooks from your browser.
I would highly recommend using git, not only for this tutorial, but for the general betterment of your life. Once git is installed, you can clone the material in this tutorial by using the git address shown above:
git clone https://github.com/EmanuelFontelles/geospatialPlot.git
If you can't or don't want to install git, there is a link above to download the contents of this repository as a zip file. I may make minor changes to the repository in the days before the tutorial, however, so cloning the repository is a much better option.
This is a personal repository that is not meant for public use at this time. It is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and noninfringement. No installation or technical support will be provided.