tables module

restee.tables

features_to_df(session, features)

Fuction to request ee.Feature or ee.FeatureCollection without coordinates as a pandas DataFrame

Parameters:

Name	Type	Description	Default
session	EESession	restee session autheticated to make requests	required
features	FeatureCollection	ee.Feature or ee.FeatureCollections to request as a DataFrame	required

Returns:

Type	Description
pandas.DataFrame	ee.FeatureCollection as DataFrame

Examples:

>>> ndvi = (
        ee.ImageCollection('MODIS/006/MOD13Q1')
        .select("NDVI")
        .first()
    )
>>> temp = ee.ImageCollection('OREGONSTATE/PRISM/AN81m')
          .filter(ee.Filter.date('2018-07-01', '2018-07-31'));

>>> states = ee.FeatureCollection('TIGER/2018/States')
>>> features = image.reduceRegions(
        collection=maine,
        reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
        scale=image.projection().nominalScale()
    )
>>> gdf = restee.features_to_geopandas(session,features)

Source code in restee/tables.py

def features_to_df(session: EESession, features: ee.FeatureCollection):
    """Fuction to request ee.Feature or ee.FeatureCollection without coordinates as a pandas DataFrame

    args:
        session (EESession): restee session autheticated to make requests
        features (ee.Feature | ee.FeatureCollection): ee.Feature or ee.FeatureCollections to
            request as a DataFrame

    returns:
        pandas.DataFrame: ee.FeatureCollection as DataFrame

    example:
        >>> ndvi = (
                ee.ImageCollection('MODIS/006/MOD13Q1')
                .select("NDVI")
                .first()
            )
        >>> temp = ee.ImageCollection('OREGONSTATE/PRISM/AN81m')
                  .filter(ee.Filter.date('2018-07-01', '2018-07-31'));

        >>> states = ee.FeatureCollection('TIGER/2018/States')
        >>> features = image.reduceRegions(
                collection=maine,
                reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
                scale=image.projection().nominalScale()
            )
        >>> gdf = restee.features_to_geopandas(session,features)
    """
    if isinstance(features, ee.Feature):
        features = ee.FeatureCollection([features])

    table = _get_table(session, features)

    return pd.read_file(StringIO(table.decode()))

features_to_file(session, features, outfile, driver='GeoJSON')

Wrapper fuction to save requested ee.Feature or ee.FeatureCollection in a vector format

Parameters:

Name	Type	Description	Default
session	EESession	restee session autheticated to make requests	required
features	FeatureCollection	ee.Feature or ee.FeatureCollections save as file	required
outfile	str	path to save features	required
driver	str	valid vector driver name to save file, see import fiona; fiona.supported_drivers for full list of supported drivers . default = "GeoJSON"	'GeoJSON'

Examples:

>>> img = (
        ee.ImageCollection('MODIS/006/MOD13Q1')
        .select("NDVI")
        .first()
    )
>>> states = ee.FeatureCollection('TIGER/2018/States')
>>> features = image.reduceRegions(
        collection=maine,
        reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
        scale=image.projection().nominalScale()
    )
>>> restee.features_to_file(session,features,"state_ndvi.geojson")

Source code in restee/tables.py

def features_to_file(
    session: EESession, features: ee.FeatureCollection, outfile: str, driver: str = "GeoJSON"
):
    """Wrapper fuction to save requested ee.Feature or ee.FeatureCollection in a vector format

    args:
        session (EESession): restee session autheticated to make requests
        features (ee.Feature | ee.FeatureCollection): ee.Feature or ee.FeatureCollections save as file
        outfile (str): path to save features
        driver (str): valid vector driver name to save file, see `import fiona; fiona.supported_drivers` 
            for full list of supported drivers . default = "GeoJSON"

    example:
        >>> img = (
                ee.ImageCollection('MODIS/006/MOD13Q1')
                .select("NDVI")
                .first()
            )
        >>> states = ee.FeatureCollection('TIGER/2018/States')
        >>> features = image.reduceRegions(
                collection=maine,
                reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
                scale=image.projection().nominalScale()
            )
        >>> restee.features_to_file(session,features,"state_ndvi.geojson")
    """
    gdf = features_to_geopandas(session, features)

    gdf.to_file(outfile,driver=driver)

    return

features_to_geodf(session, features)

Fuction to request ee.Feature or ee.FeatureCollection as a geopandas GeoDataFrame

Parameters:

Name	Type	Description	Default
session	EESession	restee session autheticated to make requests	required
features	FeatureCollection	ee.Feature or ee.FeatureCollections to request as a GeoDataFrame	required

Returns:

Type	Description
geopandas.GeoDataFrame	ee.FeatureCollection as GeoDataFrame

Examples:

>>> img = (
        ee.ImageCollection('MODIS/006/MOD13Q1')
        .select("NDVI")
        .first()
    )
>>> states = ee.FeatureCollection('TIGER/2018/States')
>>> features = image.reduceRegions(
        collection=maine,
        reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
        scale=image.projection().nominalScale()
    )
>>> gdf = restee.features_to_geopandas(session,features)

Source code in restee/tables.py

def features_to_geodf(session: EESession, features: ee.FeatureCollection):
    """Fuction to request ee.Feature or ee.FeatureCollection as a geopandas GeoDataFrame

    args:
        session (EESession): restee session autheticated to make requests
        features (ee.Feature | ee.FeatureCollection): ee.Feature or ee.FeatureCollections to
            request as a GeoDataFrame

    returns:
        geopandas.GeoDataFrame: ee.FeatureCollection as GeoDataFrame

    example:
        >>> img = (
                ee.ImageCollection('MODIS/006/MOD13Q1')
                .select("NDVI")
                .first()
            )
        >>> states = ee.FeatureCollection('TIGER/2018/States')
        >>> features = image.reduceRegions(
                collection=maine,
                reducer=ee.Reducer.mean().setOutputs(["NDVI"]),
                scale=image.projection().nominalScale()
            )
        >>> gdf = restee.features_to_geopandas(session,features)
    """
    if isinstance(features, ee.Feature):
        features = ee.FeatureCollection([features])

    table = _get_table(session, features)

    return gpd.read_file(StringIO(table.decode()))