LHC_Hidroweb is a Jupyter application for visualize ANA's Inventory and download Rainfall or Flow data from ANA's API.

You can use a ".csv" file from ANA's website, or you can get the latest Inventory file from ANA's API (and later save in your local). Don't forget to add 'Inventario.csv' at the end.

After uploading the Inventory data you can visualize the columns in the inventory.

And, check a few basic stats.

And finally you can easily download the Rainfall or Flow data with a self drawn contour or use a Shapefile. If you use the Shapefile, the file should be in WGS84.

A quick graph visualization can be done by checking the date period with some data in the Downloaded data.

Follow the process in order to utilize the Interactive Tool.

1. First, you need to open Anaconda Prompt.

2. Create a new Virtual Environment for avoid possible conflict of packages.

• Deactivate the current environment by conda deactivate.
• Check the possible environment by conda env list.
• Create by conda create --name LHC_Hidroweb python=3.7.
• Check again the environment to make sure the Environment was created conda env list.
• Activate the environment conda activate LHC_Hidroweb.

3. Core packages for the Batch download.

• Install conda install requests.

4. Core packages for the Interactive Map.

• conda install -c conda-forge jupyterlab geopandas ipywidgets nodejs ipyleaflet bqplot
• conda install numpy pandas

5. Add the newly created Virtual Environment to Jupyter

• pip install --user ipykernel
• python -m ipykernel install --user --name=LHC_Hidroweb

6. Install/Activate the widgets for Jupyter-lab

• jupyter labextension install @jupyter-widgets/jupyterlab-manager
• jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-leaflet
• jupyter labextension install bqplot

7. Opening Jupyter-lab

• jupyter-lab

• After opened the Jupyter Lab, you need to make sure to use the correct kernel.

• And, if the selected kernel is other than the one just created, selected the correct kernel.

8. Open the View_Map01.ipynb in Jupyter-lab and Run the cells

9. Enjoy the interactive map!