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GARSPandas module

GARSPandas

Source code in vgridpandas/garspandas.py 
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@pd.api.extensions.register_dataframe_accessor("gars")
class GARSPandas:
    def __init__(self, df: DataFrame):
        self._df = df

    # gars API
    # These methods simply mirror the Vgrid gars API and apply gars functions to all rows

    def latlon2gars(
        self,
        resolution: int,
        lat_col: str = "lat",
        lon_col: str = "lon",
        set_index: bool = False,
    ) -> AnyDataFrame:
        """Adds gars ID to (Geo)DataFrame.

        pd.DataFrame: uses `lat_col` and `lon_col` (default `lat` and `lon`)
        gpd.GeoDataFrame: uses `geometry`

        Assumes coordinates in epsg=4326.

        Parameters
        ----------
        resolution : int
            gars resolution
        lat_col : str
            Name of the latitude column (if used), default 'lat'
        lon_col : str
            Name of the longitude column (if used), default 'lon'
        set_index : bool
            If True, the columns with gars ID is set as index, default 'True'

        Returns
        -------
        (Geo)DataFrame with gars IDs added
        """

        if isinstance(self._df, gpd.GeoDataFrame):
            lons = self._df.geometry.x
            lats = self._df.geometry.y
        else:
            lons = self._df[lon_col]
            lats = self._df[lat_col]

        gars_ids = [
            latlon_to_gars(lat, lon, resolution) for lat, lon in zip(lats, lons)
        ]

        gars_col = GARS_COL
        assign_arg = {gars_col: gars_ids, f"{gars_col}_res": resolution}
        df = self._df.assign(**assign_arg)
        if set_index:
            return df.set_index(gars_col)
        return df

    def gars2geo(self, gars_col: str = None) -> GeoDataFrame:
        """Add geometry with GARS geometry to the DataFrame."""
        if gars_col is not None:
            if gars_col not in self._df.columns:
                raise ValueError(f"Column '{gars_col}' not found in DataFrame")
            ids = self._df[gars_col]
        else:
            if GARS_COL not in self._df.columns:
                raise ValueError(f"Column '{GARS_COL}' not found in DataFrame")
            ids = self._df[GARS_COL]
        return dggs_ids_to_geodataframe(self._df, ids, gars_to_geo)

    def garsbin(
        self,
        resolution: int,
        stats: str = "count",
        numeric_col: str = None,
        category_col: str = None,
        lat_col: str = "lat",
        lon_col: str = "lon",
    ) -> GeoDataFrame:
        """
        Bin points into gars cells and compute statistics.
        """
        gars_col = GARS_COL
        df = self.latlon2gars(resolution, lat_col, lon_col)
        result = aggregate_bin(df, gars_col, stats, numeric_col, category_col)
        return result.gars.gars2geo(gars_col=gars_col)

gars2geo(gars_col=None)

Add geometry with GARS geometry to the DataFrame.

Source code in vgridpandas/garspandas.py 
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def gars2geo(self, gars_col: str = None) -> GeoDataFrame:
    """Add geometry with GARS geometry to the DataFrame."""
    if gars_col is not None:
        if gars_col not in self._df.columns:
            raise ValueError(f"Column '{gars_col}' not found in DataFrame")
        ids = self._df[gars_col]
    else:
        if GARS_COL not in self._df.columns:
            raise ValueError(f"Column '{GARS_COL}' not found in DataFrame")
        ids = self._df[GARS_COL]
    return dggs_ids_to_geodataframe(self._df, ids, gars_to_geo)

garsbin(resolution, stats='count', numeric_col=None, category_col=None, lat_col='lat', lon_col='lon')

Bin points into gars cells and compute statistics.

Source code in vgridpandas/garspandas.py 
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def garsbin(
    self,
    resolution: int,
    stats: str = "count",
    numeric_col: str = None,
    category_col: str = None,
    lat_col: str = "lat",
    lon_col: str = "lon",
) -> GeoDataFrame:
    """
    Bin points into gars cells and compute statistics.
    """
    gars_col = GARS_COL
    df = self.latlon2gars(resolution, lat_col, lon_col)
    result = aggregate_bin(df, gars_col, stats, numeric_col, category_col)
    return result.gars.gars2geo(gars_col=gars_col)

latlon2gars(resolution, lat_col='lat', lon_col='lon', set_index=False)

Adds gars ID to (Geo)DataFrame.

pd.DataFrame: uses lat_col and lon_col (default lat and lon) gpd.GeoDataFrame: uses geometry

Assumes coordinates in epsg=4326.

Parameters

resolution : int gars resolution lat_col : str Name of the latitude column (if used), default 'lat' lon_col : str Name of the longitude column (if used), default 'lon' set_index : bool If True, the columns with gars ID is set as index, default 'True'

Returns

(Geo)DataFrame with gars IDs added

Source code in vgridpandas/garspandas.py 
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def latlon2gars(
    self,
    resolution: int,
    lat_col: str = "lat",
    lon_col: str = "lon",
    set_index: bool = False,
) -> AnyDataFrame:
    """Adds gars ID to (Geo)DataFrame.

    pd.DataFrame: uses `lat_col` and `lon_col` (default `lat` and `lon`)
    gpd.GeoDataFrame: uses `geometry`

    Assumes coordinates in epsg=4326.

    Parameters
    ----------
    resolution : int
        gars resolution
    lat_col : str
        Name of the latitude column (if used), default 'lat'
    lon_col : str
        Name of the longitude column (if used), default 'lon'
    set_index : bool
        If True, the columns with gars ID is set as index, default 'True'

    Returns
    -------
    (Geo)DataFrame with gars IDs added
    """

    if isinstance(self._df, gpd.GeoDataFrame):
        lons = self._df.geometry.x
        lats = self._df.geometry.y
    else:
        lons = self._df[lon_col]
        lats = self._df[lat_col]

    gars_ids = [
        latlon_to_gars(lat, lon, resolution) for lat, lon in zip(lats, lons)
    ]

    gars_col = GARS_COL
    assign_arg = {gars_col: gars_ids, f"{gars_col}_res": resolution}
    df = self._df.assign(**assign_arg)
    if set_index:
        return df.set_index(gars_col)
    return df