Reading and plotting¶

Read with our top-level async function.

In [4]:

import rustac

items = await rustac.read(
    "https://github.com/stac-utils/rustac-py/raw/refs/heads/main/data/100-sentinel-2-items.parquet"
)
len(items["features"])

import rustac items = await rustac.read( "https://github.com/stac-utils/rustac-py/raw/refs/heads/main/data/100-sentinel-2-items.parquet" ) len(items["features"])

Out[4]:

100

Let's take a look at some of the attributes of our STAC items.

In [5]:

import pandas
from geopandas import GeoDataFrame

data_frame = GeoDataFrame.from_features(items)
data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"])
data_frame[["geometry", "datetime", "s2:snow_ice_percentage"]]

import pandas from geopandas import GeoDataFrame data_frame = GeoDataFrame.from_features(items) data_frame["datetime"] = pandas.to_datetime(data_frame["datetime"]) data_frame[["geometry", "datetime", "s2:snow_ice_percentage"]]

Out[5]:

	geometry	datetime	s2:snow_ice_percentage
0	POLYGON ((-105.36543 39.65938, -105.34153 39.7...	2024-12-03 17:46:29.024000+00:00	3.488287
1	POLYGON ((-106.18317 40.64479, -104.88456 40.6...	2024-12-01 17:57:21.024000+00:00	47.351283
2	POLYGON ((-105.35345 39.65943, -105.33389 39.7...	2024-11-28 17:47:01.025000+00:00	56.806326
3	POLYGON ((-106.18317 40.64479, -104.88456 40.6...	2024-11-26 17:56:09.024000+00:00	0.588352
4	POLYGON ((-105.37083 39.65936, -105.34293 39.7...	2024-11-23 17:45:59.024000+00:00	0.048005
...	...	...	...
95	POLYGON ((-106.18317 40.64479, -104.88456 40.6...	2024-04-05 17:49:01.024000+00:00	48.347121
96	POLYGON ((-105.35378 39.65943, -105.34822 39.6...	2024-04-02 17:39:01.024000+00:00	4.604056
97	POLYGON ((-106.18317 40.64479, -104.88456 40.6...	2024-03-31 17:49:09.024000+00:00	23.157783
98	POLYGON ((-105.36759 39.65937, -105.33057 39.7...	2024-03-28 17:38:59.024000+00:00	3.135089
99	POLYGON ((-106.18317 40.64479, -104.88456 40.6...	2024-03-26 17:49:51.024000+00:00	32.571989

100 rows × 3 columns

How does the snow and ice percentage vary over the year?

In [3]:

from matplotlib.dates import DateFormatter

axis = data_frame.plot(x="datetime", y="s2:snow_ice_percentage", kind="scatter")
axis.xaxis.set_major_formatter(DateFormatter("%b"))

from matplotlib.dates import DateFormatter axis = data_frame.plot(x="datetime", y="s2:snow_ice_percentage", kind="scatter") axis.xaxis.set_major_formatter(DateFormatter("%b"))