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This is an old dataset - check out the newest release
here
Beta
Static dataset (Jan 2024 to Dec 2024)
Attention
This dataset is open and free to use. You can access the data in a matter of seconds by taking one of the code snippets and running it in your IDE or Jupyer notebook. Or to get some more detailed examples and walkthroughs, check out our example notebook on GitHub:
Get all data
python
df = geopandas.read_parquet("s3://weave.energy/beta/smart-meter")
Warning:
Very large file size. Please filter the data if you do not have enough RAM to run this locally.
Get data for a half hourly period
python
df = geopandas.read_parquet( "s3://weave.energy/beta/smart-meter", filters=[("data_collection_log_timestamp", "==", pd.Timestamp("2024-07-14T20:00:00Z"))]) df = df[df["total_consumption_active_import"] < 20000] df.plot(column="total_consumption_active_import" ... )
Get data within a bounding box
python
df = geopandas.read_parquet( "s3://weave.energy/beta/smart-meter", bbox=(-1.5,50.85,-1.3,50.95), filters=[("data_collection_log_timestamp", "==", pd.Timestamp("2024-07-14 20:00Z"))]) df.plot(column="total_consumption_active_import" ... )
Get data for a specific substation
python
df = geopandas.read_parquet( "s3://weave.energy/beta/smart-meter", filters=[ ("dno_alias", "==", "SSEN"), ("secondary_substation_unique_id", "==", "6400603160") ]) timeseries = df.pivot( index="data_collection_log_timestamp", columns="lv_feeder_unique_id", values="total_consumption_active_import") timeseries.resample("d").sum().plot( ... )
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Check out more detailed examples and learn how to create visualisations in our Jupyter notebook on GitHub.
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