Shapely point geometry in geopandas df to lat/lon columns

Shapely point geometry in geopandas df to lat/lon columns

To extract the latitude and longitude values from a Shapely Point geometry column in a GeoPandas DataFrame and create separate columns for them, you can use the .apply() method along with a lambda function. Here's how you can achieve this:

import geopandas as gpd # Sample GeoDataFrame with a Point geometry column named 'geometry' data = {'name': ['Point A', 'Point B', 'Point C'], 'geometry': [Point(1, 2), Point(3, 4), Point(5, 6)]} gdf = gpd.GeoDataFrame(data, geometry='geometry') # Extract latitude and longitude using .apply() and lambda function gdf['latitude'] = gdf['geometry'].apply(lambda point: point.y) gdf['longitude'] = gdf['geometry'].apply(lambda point: point.x) # Display the modified GeoDataFrame print(gdf)

In this example:

  • We create a sample GeoDataFrame with a Point geometry column named 'geometry'.
  • We use the .apply() method along with a lambda function to extract the latitude (y-coordinate) and longitude (x-coordinate) values from each Point geometry.
  • We create two new columns, 'latitude' and 'longitude', to store these extracted values.

The result will be a modified GeoDataFrame with additional 'latitude' and 'longitude' columns that contain the extracted latitude and longitude values.

Make sure you have imported the required packages, including the Point class from the shapely.geometry module, and adjust the column names and data accordingly in your specific use case.

Examples

  1. How to extract latitude and longitude from Shapely Point geometry in GeoPandas DataFrame

    • To extract latitude and longitude from Shapely Point geometry in a GeoPandas DataFrame, you can access the x and y attributes of the geometry. This example shows how to create new columns for latitude and longitude:
    pip install geopandas # Ensure geopandas is installed 
    import geopandas as gpd from shapely.geometry import Point # Create a sample GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'name': ['Location A', 'Location B'], 'geometry': [Point(12.34, 56.78), Point(98.76, 54.32)], }) # Create latitude and longitude columns gdf['longitude'] = gdf.geometry.x gdf['latitude'] = gdf.geometry.y print(gdf[['name', 'latitude', 'longitude']])

  2. How to convert Shapely Point geometry to separate lat/lon columns in GeoPandas

    • To convert Shapely Point geometry into separate latitude and longitude columns in a GeoPandas DataFrame, you can extract the x and y values. This example demonstrates how to split Point geometry into lat/lon columns:
    import geopandas as gpd from shapely.geometry import Point # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'city': ['City A', 'City B'], 'geometry': [Point(10.11, 20.22), Point(30.33, 40.44)], }) # Extract longitude and latitude into separate columns gdf['longitude'] = gdf.geometry.x gdf['latitude'] = gdf.geometry.y # Display the DataFrame with the new columns print(gdf[['city', 'latitude', 'longitude']])

  3. How to add latitude and longitude columns to an existing GeoPandas DataFrame

    • To add latitude and longitude columns to an existing GeoPandas DataFrame, extract the x and y values from the geometry. This example demonstrates adding lat/lon columns to a GeoDataFrame:
    import geopandas as gpd # Load a GeoDataFrame (from a shapefile, GeoJSON, etc.) gdf = gpd.read_file("sample_data.geojson") # Add latitude and longitude columns gdf['longitude'] = gdf.geometry.x gdf['latitude'] = gdf.geometry.y # Display the DataFrame with the added columns print(gdf[['latitude', 'longitude']])

  4. How to extract Point geometry coordinates as tuples from GeoPandas DataFrame

    • To extract coordinates as tuples from Point geometry in a GeoPandas DataFrame, you can use the apply function with a lambda expression. This example demonstrates extracting coordinates as tuples:
    import geopandas as gpd from shapely.geometry import Point # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'name': ['Site A', 'Site B'], 'geometry': [Point(11.11, 22.22), Point(33.33, 44.44)], }) # Extract coordinates as tuples gdf['coordinates'] = gdf.geometry.apply(lambda p: (p.x, p.y)) # Display the DataFrame with the coordinates as tuples print(gdf[['name', 'coordinates']])

  5. How to convert GeoPandas Point geometry to latitude and longitude in a new DataFrame

    • To create a new DataFrame with latitude and longitude extracted from a GeoPandas DataFrame, you can use the Pandas DataFrame constructor. This example shows how to create a new DataFrame with lat/lon columns:
    import pandas as pd import geopandas as gpd from shapely.geometry import Point # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'place': ['Place A', 'Place B'], 'geometry': [Point(15.16, 25.26), Point(35.36, 45.46)], }) # Create a new DataFrame with lat/lon columns df = pd.DataFrame({ 'place': gdf['place'], 'latitude': gdf.geometry.y, 'longitude': gdf.geometry.x, }) # Display the new DataFrame print(df)

  6. How to convert Shapely Point geometry to separate latitude and longitude in CSV

    • To save latitude and longitude from Point geometry in a GeoPandas DataFrame to a CSV file, you can extract the lat/lon columns and use to_csv. This example demonstrates saving to CSV:
    import geopandas as gpd from shapely.geometry import Point # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'location': ['Location X', 'Location Y'], 'geometry': [Point(21.21, 31.31), Point(41.41, 51.51)], }) # Add latitude and longitude columns gdf['longitude'] = gdf.geometry.x gdf['latitude'] = gdf.geometry.y # Save to CSV gdf[['location', 'latitude', 'longitude']].to_csv("locations.csv", index=False)

  7. How to check if Shapely Point geometry in GeoPandas DataFrame has valid coordinates

    • To ensure Point geometry in a GeoPandas DataFrame has valid coordinates, you can check if the geometry is not null and has a defined location. This example demonstrates validation:
    import geopandas as gpd import pandas as pd from shapely.geometry import Point # Create a GeoDataFrame with some invalid geometry gdf = gpd.GeoDataFrame({ 'name': ['Place A', 'Place B', 'Place C'], 'geometry': [Point(12.12, 23.23), None, Point(34.34, 45.45)], }) # Check for valid coordinates gdf['valid'] = gdf.geometry.apply(lambda geom: geom is not None and not geom.is_empty) # Display the DataFrame with validity check print(gdf[['name', 'valid']])

  8. How to convert Shapely Point geometry to GeoJSON and extract lat/lon in GeoPandas

    • To convert Shapely Point geometry to GeoJSON and extract latitude/longitude, you can use the __geo_interface__ method and convert the coordinates. This example demonstrates the conversion:
    import geopandas as gpd from shapely.geometry import Point # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'region': ['Region A', 'Region B'], 'geometry': [Point(25.25, 35.35), Point(45.45, 55.55)], }) # Convert to GeoJSON and extract lat/lon geojson = gdf.__geo_interface__ coordinates = [feature['geometry']['coordinates'] for feature in geojson['features']] # Display the coordinates extracted from GeoJSON print(coordinates) # Outputs: [[25.25, 35.35], [45.45, 55.55]]

  9. How to convert Shapely Point geometry to WKT and extract lat/lon in GeoPandas

    • To convert Shapely Point geometry to Well-Known Text (WKT) and extract latitude/longitude, you can use the wkt module from shapely. This example demonstrates the conversion and extraction:
    import geopandas as gpd from shapely.geometry import Point from shapely.wkt import dumps # Import WKT conversion # Create a GeoDataFrame with Point geometry gdf = gpd.GeoDataFrame({ 'location': ['Location A', 'Location B'], 'geometry': [Point(13.13, 23.23), Point(33.33, 43.43)], }) # Convert to WKT and extract lat/lon wkt_strings = gdf['geometry'].apply(dumps) lat_lon = [wkt_str.replace("POINT ", "").strip("()").split() for wkt_str in wkt_strings] # Convert to float and display extracted coordinates lat_lon = [[float(x), float(y)] for x, y in lat_lon] print(lat_lon) # Outputs: [[13.13, 23.23], [33.33, 43.43]]

  10. How to ensure Shapely Point geometry has valid latitude and longitude in GeoPandas

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