#!/usr/bin/env python
# coding: utf-8

# # Introduction to Unfolded Map SDK
# 
# [![open_in_colab][colab_badge]][colab_notebook_link]
# [![open_in_binder][binder_badge]][binder_notebook_link]
# 
# [colab_badge]: https://colab.research.google.com/assets/colab-badge.svg
# [colab_notebook_link]: https://colab.research.google.com/github/foursquare/unfolded-sdk-examples/blob/master/notebooks/01%20-%20Introduction.ipynb
# [binder_badge]: https://mybinder.org/badge_logo.svg
# [binder_notebook_link]: https://mybinder.org/v2/gh/foursquare/unfolded-sdk-examples/master?urlpath=lab/tree/notebooks/01%20-%20Introduction.ipynb

# This notebook demonstrates how to create a local Unfolded map and then how to add a simple dataset to it.

# ## Dependencies
# 
# This notebook requires the following Python dependencies:
# 
# - `unfolded.map-sdk`: The Unfolded Map SDK
# - `sidecar`: Jupyter sidecar widget to allow rendering Unfolded Studio in a sidebar.
# - `pandas`: DataFrame library
# 
# If running this notebook in Binder, these dependencies should already be installed. If running in Colab, the next cell will install these dependencies.

# In[ ]:


# If in Colab, install this notebook's required dependencies
import sys
if "google.colab" in sys.modules:
    get_ipython().system("pip install 'unfolded.map_sdk>=1.0' sidecar pandas")


# ## Imports

# In[ ]:


from unfolded.map_sdk import create_map
from sidecar import Sidecar
import pandas as pd


# ## Creating a Map

# First, let's create a map instance:

# In[ ]:


unfolded_map = create_map()


# In environments that support Jupyter Widgets, such as Jupyter Notebook, JupyterLab, and Google Colab, simply put the map variable as the last or only line in a cell:

# In[ ]:


unfolded_map


# In Jupyter Lab we also have the option of displaying a map as a separate side pane using the [`Sidecar`](https://github.com/jupyter-widgets/jupyterlab-sidecar) package. In other environments than Jupyter Lab, using `sidecar` will probably not work.

# In[ ]:


sc = Sidecar(title='Unfolded Map', anchor='split-right')
with sc:
    display(unfolded_map)


# ## Adding data

# We can now add a dataframe as a dataset to the map: 

# In[ ]:


unfolded_map.add_dataset({
    'data': pd.DataFrame({
        'City': ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas'],
        'Country': ['Argentina', 'Brazil', 'Chile', 'Colombia', 'Venezuela'],
        'Latitude': [-34.58, -15.78, -33.45, 4.60, 10.48],
        'Longitude': [-58.66, -47.91, -70.66, -74.08, -66.86]
    })
})


# ## Set view state

# Now let's change the map viewport to better see the data points we just added:

# In[ ]:


unfolded_map.set_view({
    'longitude': -60, 
    'latitude': -20,
    'zoom': 2
})


# There are many more things you can control in Unfolded maps via the SDK. Check out the rest of the examples in this directory.