InĀ [1]:
import pydeck as pdk
import pandas as pd

Plotting lights at night¶

NASA has collected global light emission data for over 30 years. The data set is a deeply fascinating one and has been used for news stories on the Syrian Civil War [1], North Korea [2], and economic growth [3].

In this notebook, we'll use a deck.gl HeatmapLayer to visualize some of the changes at different points in time.

Getting the data¶

The data for Chengdu, China, is cleaned and available below. Please note this data is meant for demonstration only.

InĀ [2]:
LIGHTS_URL = 'https://raw.githubusercontent.com/ajduberstein/lights_at_night/master/chengdu_lights_at_night.csv'
df = pd.read_csv(LIGHTS_URL)
df.head()
Out[2]:
year lng lat brightness
0 1993 104.575 31.808 4
1 1993 104.583 31.808 4
2 1993 104.592 31.808 4
3 1993 104.600 31.808 4
4 1993 104.675 31.808 4

Setting the colors¶

pydeck does need to know the color for this data in advance of plotting it

InĀ [3]:
df['color'] = df['brightness'].apply(lambda val: [255, val * 4,  255, 255])
df.sample(10)
Out[3]:
year lng lat brightness color
253616 2011 103.475 29.792 5 [255, 20, 255, 255]
198401 2007 103.508 30.650 4 [255, 16, 255, 255]
178981 2013 105.058 29.608 59 [255, 236, 255, 255]
226082 2011 105.058 31.167 5 [255, 20, 255, 255]
230962 2011 103.833 30.925 12 [255, 48, 255, 255]
202332 2007 105.700 30.492 3 [255, 12, 255, 255]
269887 2005 103.583 31.000 13 [255, 52, 255, 255]
20071 1997 103.692 31.058 5 [255, 20, 255, 255]
125365 2003 104.167 30.967 5 [255, 20, 255, 255]
308091 1999 103.875 30.775 11 [255, 44, 255, 255]

Plotting and interacting¶

We can plot this data set of light brightness by year, configuring a slider to filter the data as below:

InĀ [4]:
plottable = df[df['year'] == 1993].to_dict(orient='records')

view_state = pdk.ViewState(
    latitude=31.0,
    longitude=104.5,
    zoom=8)
scatterplot = pdk.Layer(
    'HeatmapLayer',
    data=plottable,
    get_position=['lng', 'lat'],
    get_weight='brightness',
    opacity=0.5,
    pickable=False,
    get_radius=800)
r = pdk.Deck(
    layers=[scatterplot],
    initial_view_state=view_state,
    views=[pdk.View(type='MapView', controller=None)])
r.show()
Out[4]:
InĀ [5]:
import ipywidgets as widgets
from IPython.display import display
slider = widgets.IntSlider(1992, min=1993, max=2013, step=2)
def on_change(v):
    results = df[df['year'] == slider.value].to_dict(orient='records')
    scatterplot.data = results
    r.update()
    
slider.observe(on_change, names='value')
display(slider)