Add convert_to_gdf function

leafmap/common.py

@@ -18,18 +18,16 @@
 import whitebox
 import subprocess
 from pathlib import Path
-from typing import Union, List, Dict, Optional, Tuple
+from typing import Union, List, Dict, Optional, Tuple, TYPE_CHECKING
 from .stac import *
 
 try:
-    from IPython.display import display, IFrame
+    from IPython.display import display
 except ImportError:
     pass
 
-try:
+if TYPE_CHECKING:
     import geopandas as gpd
-except ImportError:
-    gpd = None
 
 
 class WhiteboxTools(whitebox.WhiteboxTools):
@@ -104,7 +102,7 @@ def set_proxy(
     try:
         response = requests.get("https://google.com")
         response.raise_for_status()
-    except requests.exceptions.RequestException as error_requests:
+    except requests.exceptions.RequestException as e:
         print(
             "Failed to connect to Google Services. "
             "Please double check the port number and IP address."
@@ -421,7 +419,7 @@ def display_html(
     else:
         raise ValueError("Invalid input type. Expected a file path or an HTML string.")
 
-    display(IFrame(srcdoc=html_content, width=width, height=height))
+    display(IFrame(src=html_content, width=width, height=height))
 
 
 def has_transparency(img) -> bool:
@@ -2492,19 +2490,6 @@ def to_hex_colors(colors):
         return colors
 
 
-def display_html(src, width=950, height=600):
-    """Display an HTML file in a Jupyter Notebook.
-
-    Args
-        src (str): File path to HTML file.
-        width (int, optional): Width of the map. Defaults to 950.
-        height (int, optional): Height of the map. Defaults to 600.
-    """
-    if not os.path.isfile(src):
-        raise ValueError(f"{src} is not a valid file path.")
-    display(IFrame(src=src, width=width, height=height))
-
-
 def get_census_dict(reset=False):
     """Returns a dictionary of Census data.
 
@@ -14146,3 +14131,108 @@ def d2s_tile(
             return f"{url}?API_KEY={api_key}"
     else:
         return url
+
+
+def convert_to_gdf(
+    data: Union[pd.DataFrame, str],
+    geometry: Optional[str] = None,
+    lat: Optional[str] = None,
+    lon: Optional[str] = None,
+    crs: str = "EPSG:4326",
+    included: Optional[List[str]] = None,
+    excluded: Optional[List[str]] = None,
+    obj_to_str: bool = False,
+    open_args: Optional[Dict[str, Any]] = None,
+    **kwargs: Any,
+) -> "gpd.GeoDataFrame":
+    """Convert data to a GeoDataFrame.
+
+    Args:
+        data (Union[pd.DataFrame, str]): The input data, either as a DataFrame or a file path.
+        geometry (Optional[str], optional): The column name containing geometry data. Defaults to None.
+        lat (Optional[str], optional): The column name containing latitude data. Defaults to None.
+        lon (Optional[str], optional): The column name containing longitude data. Defaults to None.
+        crs (str, optional): The coordinate reference system to use. Defaults to "EPSG:4326".
+        included (Optional[List[str]], optional): List of columns to include. Defaults to None.
+        excluded (Optional[List[str]], optional): List of columns to exclude. Defaults to None.
+        obj_to_str (bool, optional): Whether to convert object dtype columns to string. Defaults to False.
+        open_args (Optional[Dict[str, Any]], optional): Additional arguments for file opening functions. Defaults to None.
+        **kwargs (Any): Additional keyword arguments for GeoDataFrame creation.
+
+    Returns:
+        gpd.GeoDataFrame: The converted GeoDataFrame.
+
+    Raises:
+        ValueError: If the file format is unsupported or required columns are not provided.
+    """
+    import geopandas as gpd
+    from shapely.geometry import Point, shape
+
+    if open_args is None:
+        open_args = {}
+
+    if not isinstance(data, pd.DataFrame):
+        if isinstance(data, str):
+            if data.endswith(".parquet"):
+                data = pd.read_parquet(data, **open_args)
+            elif data.endswith(".csv"):
+                data = pd.read_csv(data, **open_args)
+            elif data.endswith(".json"):
+                data = pd.read_json(data, **open_args)
+            elif data.endswith(".xlsx"):
+                data = pd.read_excel(data, **open_args)
+            else:
+                raise ValueError(
+                    "Unsupported file format. Only Parquet, CSV, JSON, and Excel files are supported."
+                )
+
+    # If include_cols is specified, filter the DataFrame to include only those columns
+    if included:
+        if geometry:
+            included.append(geometry)
+        elif lat and lon:
+            included.append(lat)
+            included.append(lon)
+        data = data[included]
+
+    # Exclude specified columns if provided
+    if excluded:
+        data = data.drop(columns=excluded)
+
+    # Convert 'object' dtype columns to 'string' if obj_to_str is True
+    if obj_to_str:
+        data = data.astype(
+            {col: "string" for col in data.select_dtypes(include="object").columns}
+        )
+
+    # Handle the creation of geometry
+    if geometry:
+
+        def convert_geometry(x):
+            if isinstance(x, str):
+                try:
+                    # Parse the string as JSON and then convert to a geometry
+                    return shape(json.loads(x))
+                except (json.JSONDecodeError, TypeError) as e:
+                    print(f"Error converting geometry: {e}")
+                    return None
+            return x
+
+        data = data[data[geometry].notnull()]
+        data[geometry] = data[geometry].apply(convert_geometry)
+    elif lat and lon:
+        # Create a geometry column from latitude and longitude
+        data["geometry"] = data.apply(lambda row: Point(row[lon], row[lat]), axis=1)
+        geometry = "geometry"
+    else:
+        raise ValueError(
+            "Either geometry_col or both lat_col and lon_col must be provided."
+        )
+
+    # Convert the DataFrame to a GeoDataFrame
+    gdf = gpd.GeoDataFrame(data, geometry=geometry, **kwargs)
+
+    # Set CRS (assuming WGS84 by default, modify as needed)
+    gdf.set_crs(crs, inplace=True)
+
+    return gdf

leafmap/leafmap.py

@@ -211,39 +211,39 @@ def handle_draw(target, action, geo_json):
         if "catalog_source" in kwargs:
             self.set_catalog_source(kwargs["catalog_source"])
 
-    def add(self, object, index=None, **kwargs) -> None:
+    def add(self, obj, index=None, **kwargs) -> None:
         """Adds a layer to the map.
 
         Args:
             layer (object): The layer to add to the map.
             index (int, optional): The index at which to add the layer. Defaults to None.
         """
-        if isinstance(object, str):
-            if object in basemaps.keys():
-                object = get_basemap(object)
+        if isinstance(obj, str):
+            if obj in basemaps.keys():
+                obj = get_basemap(obj)
             else:
-                if object == "nasa_earth_data":
+                if obj == "nasa_earth_data":
                     from .toolbar import nasa_data_gui
 
                     nasa_data_gui(self, **kwargs)
-                elif object == "inspector":
+                elif obj == "inspector":
                     from .toolbar import inspector_gui
 
                     inspector_gui(self, **kwargs)
 
-                elif object == "stac":
+                elif obj == "stac":
                     self.add_stac_gui(**kwargs)
-                elif object == "basemap":
+                elif obj == "basemap":
                     self.add_basemap_gui(**kwargs)
-                elif object == "inspector":
+                elif obj == "inspector":
                     self.add_inspector_gui(**kwargs)
-                elif object == "layer_manager":
+                elif obj == "layer_manager":
                     self.add_layer_manager(**kwargs)
-                elif object == "oam":
+                elif obj == "oam":
                     self.add_oam_gui(**kwargs)
                 return
 
-        super().add(object, index=index)
+        super().add(obj, index=index)
 
         if hasattr(self, "layer_manager_widget"):
             self.update_layer_manager()