Nighttime Lights in Myanmar

Data & Methodology Note:

This notebook uses VIIRS Nighttime Lights Collection 2 monthly and annual products. For all analyses and visualizations where the year 2025 is shown, monthly data are aggregated to the annual level to ensure completeness, as the official annual product for 2025 may not be available yet. All other years use the official annual product where possible.

/var/folders/gs/_227cnyd0pq1fr817_0jbcyw0000gp/T/ipykernel_87311/1568446717.py:19: UserWarning: Glyph 8594 (\N{RIGHTWARDS ARROW}) missing from font(s) Open Sans.
  plt.tight_layout()
/Users/ssarva/Library/Python/3.13/lib/python/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 8594 (\N{RIGHTWARDS ARROW}) missing from font(s) Open Sans.
  fig.canvas.print_figure(bytes_io, **kw)

ntl_annual_adm1["date"] = pd.to_datetime(ntl_annual_adm1["date"])
ntl_annual_adm1["year"] = ntl_annual_adm1["date"].dt.year

ntl_monthly_adm1["date"] = pd.to_datetime(ntl_monthly_adm1["date"])
ntl_monthly_agg_adm1 = (
    ntl_monthly_adm1.groupby(
        ["ADM1_PCODE", "ADM1_EN", pd.Grouper(key="date", freq="YS")]
    )["ntl_sum"]
    .mean()
    .reset_index()
)
ntl_monthly_agg_adm1["year"] = ntl_monthly_agg_adm1["date"].dt.year