{"id":1127319,"date":"2025-01-08T20:09:15","date_gmt":"2025-01-08T12:09:15","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1127319.html"},"modified":"2025-01-08T20:09:18","modified_gmt":"2025-01-08T12:09:18","slug":"python%e5%a6%82%e4%bd%95%e6%8a%8a%e5%87%a0%e4%b8%87%e4%b8%aa%e5%9b%be%e6%96%91%e5%90%88%e5%b9%b6-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1127319.html","title":{"rendered":"python\u5982\u4f55\u628a\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25094341\/49bdeaa0-c790-40ff-b5f6-6e768678219a.webp\" alt=\"python\u5982\u4f55\u628a\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76\" \/><\/p>\n<p><p> <strong>Python\u5982\u4f55\u628a\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76<\/strong><\/p>\n<\/p>\n<p><p><strong>\u4f7f\u7528Python\u5c06\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff1a\u4f7f\u7528Shapely\u5e93\u8fdb\u884c\u51e0\u4f55\u64cd\u4f5c\u3001\u4f7f\u7528GeoPandas\u5e93\u5904\u7406\u5730\u7406\u6570\u636e\u3001\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u63d0\u9ad8\u6548\u7387\u3002<\/strong> \u5176\u4e2d\uff0cGeoPandas\u5e93\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5904\u7406\u548c\u5206\u6790\u5730\u7406\u6570\u636e\u3002\u5b83\u57fa\u4e8ePandas\u5e93\u548cShapely\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5730\u7406\u6570\u636e\u64cd\u4f5c\u529f\u80fd\u3002\u5728\u8be6\u7ec6\u63cf\u8ff0GeoPandas\u5e93\u4e4b\u524d\uff0c\u6211\u4eec\u5148\u7b80\u5355\u4e86\u89e3\u4e00\u4e0b\u5176\u4ed6\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><p>GeoPandas\u5e93\u662f\u4e00\u4e2a\u57fa\u4e8ePandas\u548cShapely\u7684Python\u5e93\uff0c\u4e13\u95e8\u7528\u4e8e\u5904\u7406\u5730\u7406\u6570\u636e\u3002\u5b83\u6269\u5c55\u4e86Pandas\u7684\u6570\u636e\u7ed3\u6784\uff0c\u4f7f\u5176\u80fd\u591f\u5904\u7406\u5730\u7406\u6570\u636e\u7c7b\u578b\uff0c\u5982\u70b9\u3001\u591a\u8fb9\u5f62\u548c\u7ebf\u3002GeoPandas\u63d0\u4f9b\u4e86\u8bb8\u591a\u4fbf\u6377\u7684\u51fd\u6570\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u8fdb\u884c\u5730\u7406\u6570\u636e\u7684\u8bfb\u53d6\u3001\u5199\u5165\u3001\u8f6c\u6362\u548c\u5206\u6790\u64cd\u4f5c\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528GeoPandas\u5e93\u6765\u5408\u5e76\u51e0\u4e07\u4e2a\u56fe\u6591\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5b89\u88c5\u548c\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n<p><p>\u5728\u5f00\u59cb\u5904\u7406\u5730\u7406\u6570\u636e\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u548c\u5bfc\u5165\u4e00\u4e9b\u5fc5\u8981\u7684\u5e93\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">!pip install geopandas shapely fiona pyproj<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><pre><code class=\"language-python\">import geopandas as gpd<\/p>\n<p>from shapely.geometry import Polygon<\/p>\n<p>import multiprocessing<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u8bfb\u53d6\u5730\u7406\u6570\u636e<\/h3>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6\u5730\u7406\u6570\u636e\u6587\u4ef6\u3002GeoPandas\u652f\u6301\u591a\u79cd\u5730\u7406\u6570\u636e\u683c\u5f0f\uff0c\u5982Shapefile\u3001GeoJSON\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u8bfb\u53d6Shapefile\u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">gdf = gpd.read_file(&#39;path_to_your_shapefile.shp&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u5408\u5e76\u56fe\u6591<\/h3>\n<\/p>\n<p><h4>1\u3001\u4f7f\u7528GeoPandas\u8fdb\u884c\u5408\u5e76<\/h4>\n<\/p>\n<p><p>GeoPandas\u63d0\u4f9b\u4e86\u4e00\u4e2a\u975e\u5e38\u65b9\u4fbf\u7684\u51fd\u6570<code>dissolve<\/code>\uff0c\u53ef\u4ee5\u5c06\u5730\u7406\u6570\u636e\u6309\u7167\u6307\u5b9a\u7684\u5217\u8fdb\u884c\u5408\u5e76\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5c06\u6240\u6709\u56fe\u6591\u5408\u5e76\u4e3a\u4e00\u4e2a\u591a\u8fb9\u5f62<\/p>\n<p>merged_gdf = gdf.dissolve()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u4f7f\u7528Shapely\u5e93\u8fdb\u884c\u51e0\u4f55\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u9700\u8981\u66f4\u7075\u6d3b\u7684\u5408\u5e76\u64cd\u4f5c\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Shapely\u5e93\u4e2d\u7684<code>unary_union<\/code>\u51fd\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from shapely.ops import unary_union<\/p>\n<h2><strong>\u5c06\u6240\u6709\u591a\u8fb9\u5f62\u5408\u5e76\u4e3a\u4e00\u4e2a\u591a\u8fb9\u5f62<\/strong><\/h2>\n<p>merged_polygon = unary_union(gdf.geometry)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u63d0\u9ad8\u6548\u7387<\/h3>\n<\/p>\n<p><p>\u5904\u7406\u51e0\u4e07\u4e2a\u56fe\u6591\u53ef\u80fd\u4f1a\u6bd4\u8f83\u8017\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u6765\u63d0\u9ad8\u6548\u7387\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def merge_polygons(polygons):<\/p>\n<p>    return unary_union(polygons)<\/p>\n<h2><strong>\u5c06\u5730\u7406\u6570\u636e\u5206\u6210\u591a\u4e2a\u5b50\u96c6<\/strong><\/h2>\n<p>chunks = [gdf.geometry[i:i+1000] for i in range(0, len(gdf), 1000)]<\/p>\n<h2><strong>\u4f7f\u7528\u591a\u8fdb\u7a0b\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97<\/strong><\/h2>\n<p>with multiprocessing.Pool() as pool:<\/p>\n<p>    merged_chunks = pool.map(merge_polygons, chunks)<\/p>\n<h2><strong>\u5c06\u5408\u5e76\u540e\u7684\u5b50\u96c6\u518d\u6b21\u5408\u5e76<\/strong><\/h2>\n<p>final_merged_polygon = unary_union(merged_chunks)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u4fdd\u5b58\u7ed3\u679c<\/h3>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u5408\u5e76\u540e\u7684\u7ed3\u679c\u4fdd\u5b58\u4e3a\u65b0\u7684\u5730\u7406\u6570\u636e\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4fdd\u5b58\u4e3aShapefile\u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u65b0\u7684GeoDataFrame<\/p>\n<p>merged_gdf = gpd.GeoDataFrame(geometry=[final_merged_polygon])<\/p>\n<h2><strong>\u4fdd\u5b58\u4e3aShapefile\u6587\u4ef6<\/strong><\/h2>\n<p>merged_gdf.to_file(&#39;path_to_save_merged_shapefile.shp&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4f7f\u7528GeoPandas\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u4fdd\u5b58\u5730\u7406\u6570\u636e\uff0c\u5e76\u901a\u8fc7<code>dissolve<\/code>\u51fd\u6570\u548cShapely\u5e93\u4e2d\u7684<code>unary_union<\/code>\u51fd\u6570\u6765\u5408\u5e76\u51e0\u4e07\u4e2a\u56fe\u6591\u3002\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u53ef\u4ee5\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6548\u7387\u3002GeoPandas\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5730\u7406\u6570\u636e\u64cd\u4f5c\u529f\u80fd\uff0c\u4f7f\u5f97\u5904\u7406\u5730\u7406\u6570\u636e\u53d8\u5f97\u975e\u5e38\u7b80\u5355\u548c\u9ad8\u6548\u3002<\/p>\n<\/p>\n<p><h3>\u4e03\u3001\u5b9e\u9645\u6848\u4f8b<\/h3>\n<\/p>\n<p><p>\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u4f7f\u7528Python\u5408\u5e76\u51e0\u4e07\u4e2a\u56fe\u6591\uff0c\u6211\u4eec\u6765\u770b\u4e00\u4e2a\u5b9e\u9645\u6848\u4f8b\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u51e0\u4e07\u4e2a\u56fe\u6591\u7684Shapefile\u6587\u4ef6\uff0c\u6211\u4eec\u9700\u8981\u5c06\u8fd9\u4e9b\u56fe\u6591\u5408\u5e76\u4e3a\u4e00\u4e2a\u591a\u8fb9\u5f62\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u4ee3\u7801\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import geopandas as gpd<\/p>\n<p>from shapely.ops import unary_union<\/p>\n<p>import multiprocessing<\/p>\n<h2><strong>\u8bfb\u53d6\u5730\u7406\u6570\u636e<\/strong><\/h2>\n<p>gdf = gpd.read_file(&#39;path_to_your_shapefile.shp&#39;)<\/p>\n<h2><strong>\u5c06\u5730\u7406\u6570\u636e\u5206\u6210\u591a\u4e2a\u5b50\u96c6<\/strong><\/h2>\n<p>chunks = [gdf.geometry[i:i+1000] for i in range(0, len(gdf), 1000)]<\/p>\n<h2><strong>\u5b9a\u4e49\u5408\u5e76\u51fd\u6570<\/strong><\/h2>\n<p>def merge_polygons(polygons):<\/p>\n<p>    return unary_union(polygons)<\/p>\n<h2><strong>\u4f7f\u7528\u591a\u8fdb\u7a0b\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97<\/strong><\/h2>\n<p>with multiprocessing.Pool() as pool:<\/p>\n<p>    merged_chunks = pool.map(merge_polygons, chunks)<\/p>\n<h2><strong>\u5c06\u5408\u5e76\u540e\u7684\u5b50\u96c6\u518d\u6b21\u5408\u5e76<\/strong><\/h2>\n<p>final_merged_polygon = unary_union(merged_chunks)<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u65b0\u7684GeoDataFrame<\/strong><\/h2>\n<p>merged_gdf = gpd.GeoDataFrame(geometry=[final_merged_polygon])<\/p>\n<h2><strong>\u4fdd\u5b58\u4e3aShapefile\u6587\u4ef6<\/strong><\/h2>\n<p>merged_gdf.to_file(&#39;path_to_save_merged_shapefile.shp&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516b\u3001\u6df1\u5165\u7406\u89e3GeoPandas\u548cShapely<\/h3>\n<\/p>\n<p><h4>1\u3001GeoPandas\u7684\u6570\u636e\u7ed3\u6784<\/h4>\n<\/p>\n<p><p>GeoPandas\u6269\u5c55\u4e86Pandas\u7684\u6570\u636e\u7ed3\u6784\uff0c\u4f7f\u5176\u80fd\u591f\u5904\u7406\u5730\u7406\u6570\u636e\u7c7b\u578b\u3002GeoDataFrame\u662fGeoPandas\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\uff0c\u5b83\u7ee7\u627f\u4e86Pandas\u7684DataFrame\uff0c\u5e76\u6dfb\u52a0\u4e86\u4e00\u4e2a<code>geometry<\/code>\u5217\uff0c\u7528\u4e8e\u5b58\u50a8\u5730\u7406\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u521b\u5efaGeoDataFrame\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import geopandas as gpd<\/p>\n<p>from shapely.geometry import Point, Polygon<\/p>\n<h2><strong>\u521b\u5efa\u70b9\u548c\u591a\u8fb9\u5f62<\/strong><\/h2>\n<p>point = Point(1, 1)<\/p>\n<p>polygon = Polygon([(0, 0), (1, 1), (1, 0)])<\/p>\n<h2><strong>\u521b\u5efaGeoDataFrame<\/strong><\/h2>\n<p>gdf = gpd.GeoDataFrame({&#39;geometry&#39;: [point, polygon]})<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001Shapely\u7684\u51e0\u4f55\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>Shapely\u662f\u4e00\u4e2a\u7528\u4e8e\u64cd\u4f5c\u548c\u5206\u6790\u51e0\u4f55\u5bf9\u8c61\u7684Python\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u51e0\u4f55\u64cd\u4f5c\u51fd\u6570\uff0c\u5982<code>union<\/code>\u3001<code>intersection<\/code>\u3001<code>difference<\/code>\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u51e0\u4f55\u64cd\u4f5c\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from shapely.geometry import Point, Polygon<\/p>\n<h2><strong>\u521b\u5efa\u70b9\u548c\u591a\u8fb9\u5f62<\/strong><\/h2>\n<p>point = Point(1, 1)<\/p>\n<p>polygon = Polygon([(0, 0), (1, 1), (1, 0)])<\/p>\n<h2><strong>\u8ba1\u7b97\u7f13\u51b2\u533a<\/strong><\/h2>\n<p>buffer = point.buffer(1)<\/p>\n<h2><strong>\u8ba1\u7b97\u4ea4\u96c6<\/strong><\/h2>\n<p>intersection = polygon.intersection(buffer)<\/p>\n<h2><strong>\u8ba1\u7b97\u5e76\u96c6<\/strong><\/h2>\n<p>union = polygon.union(buffer)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e5d\u3001\u6700\u4f73\u5b9e\u8df5<\/h3>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5730\u7406\u6570\u636e\u65f6\uff0c\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6700\u4f73\u5b9e\u8df5\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u683c\u5f0f<\/h4>\n<\/p>\n<p><p>\u4e0d\u540c\u7684\u5730\u7406\u6570\u636e\u683c\u5f0f\u6709\u4e0d\u540c\u7684\u4f18\u7f3a\u70b9\u3002\u5728\u9009\u62e9\u6570\u636e\u683c\u5f0f\u65f6\uff0c\u5e94\u8003\u8651\u6570\u636e\u7684\u5927\u5c0f\u3001\u590d\u6742\u6027\u548c\u4f7f\u7528\u573a\u666f\u3002\u5e38\u89c1\u7684\u5730\u7406\u6570\u636e\u683c\u5f0f\u5305\u62ecShapefile\u3001GeoJSON\u548cKML\u7b49\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u4f18\u5316\u6570\u636e\u5904\u7406\u6d41\u7a0b<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u89c4\u6a21\u5730\u7406\u6570\u636e\u65f6\uff0c\u5e94\u5c3d\u91cf\u4f18\u5316\u6570\u636e\u5904\u7406\u6d41\u7a0b\uff0c\u4ee5\u63d0\u9ad8\u6548\u7387\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u3001\u5206\u5757\u5904\u7406\u7b49\u6280\u672f\u6765\u52a0\u5feb\u6570\u636e\u5904\u7406\u901f\u5ea6\u3002<\/p>\n<\/p>\n<p><h4>3\u3001\u6ce8\u610f\u6570\u636e\u7684\u7cbe\u5ea6\u548c\u8303\u56f4<\/h4>\n<\/p>\n<p><p>\u5728\u8fdb\u884c\u5730\u7406\u6570\u636e\u64cd\u4f5c\u65f6\uff0c\u5e94\u6ce8\u610f\u6570\u636e\u7684\u7cbe\u5ea6\u548c\u8303\u56f4\uff0c\u4ee5\u786e\u4fdd\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002\u4f8b\u5982\uff0c\u5728\u8fdb\u884c\u51e0\u4f55\u64cd\u4f5c\u65f6\uff0c\u5e94\u786e\u4fdd\u8f93\u5165\u6570\u636e\u7684\u5750\u6807\u7cfb\u4e00\u81f4\u3002<\/p>\n<\/p>\n<p><h3>\u5341\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u8be6\u7ec6\u4e86\u89e3\u4e86\u5982\u4f55\u4f7f\u7528Python\u5408\u5e76\u51e0\u4e07\u4e2a\u56fe\u6591\u3002\u901a\u8fc7\u4f7f\u7528GeoPandas\u5e93\u548cShapely\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u4fdd\u5b58\u5730\u7406\u6570\u636e\uff0c\u5e76\u901a\u8fc7<code>dissolve<\/code>\u51fd\u6570\u548c<code>unary_union<\/code>\u51fd\u6570\u6765\u5408\u5e76\u56fe\u6591\u3002\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u53ef\u4ee5\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6548\u7387\u3002\u540c\u65f6\uff0c\u6211\u4eec\u8fd8\u4ecb\u7ecd\u4e86\u4e00\u4e9b\u6700\u4f73\u5b9e\u8df5\uff0c\u5e2e\u52a9\u8bfb\u8005\u66f4\u597d\u5730\u5904\u7406\u5730\u7406\u6570\u636e\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u5de5\u5177\uff0c\u4ee5\u5b9e\u73b0\u9ad8\u6548\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u5408\u5e76\u5927\u91cf\u56fe\u6591\u6570\u636e\uff1f<\/strong><br \/>\u5408\u5e76\u51e0\u4e07\u4e2a\u56fe\u6591\u6570\u636e\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684Geopandas\u5e93\u3002Geopandas\u5141\u8bb8\u7528\u6237\u8f7b\u677e\u5904\u7406\u548c\u5206\u6790\u5730\u7406\u6570\u636e\u3002\u53ef\u4ee5\u901a\u8fc7\u8bfb\u53d6\u591a\u4e2a\u56fe\u6591\u6587\u4ef6\uff08\u5982Shapefile\u6216GeoJSON\uff09\uff0c\u4f7f\u7528<code>gpd.concat()<\/code>\u51fd\u6570\u5c06\u5b83\u4eec\u5408\u5e76\u6210\u4e00\u4e2a\u5355\u4e00\u7684GeoDataFrame\uff0c\u7136\u540e\u4f7f\u7528<code>to_file()<\/code>\u65b9\u6cd5\u5c06\u5408\u5e76\u540e\u7684\u6570\u636e\u4fdd\u5b58\u4e3a\u65b0\u6587\u4ef6\u3002<\/p>\n<p><strong>\u5408\u5e76\u56fe\u6591\u6570\u636e\u65f6\uff0c\u6027\u80fd\u4f18\u5316\u6709\u54ea\u4e9b\u5efa\u8bae\uff1f<\/strong><br \/>\u5728\u5904\u7406\u5927\u91cf\u6570\u636e\u65f6\uff0c\u6027\u80fd\u4f18\u5316\u662f\u5173\u952e\u3002\u53ef\u4ee5\u8003\u8651\u4f7f\u7528Dask\u6765\u5904\u7406\u6570\u636e\uff0cDask\u80fd\u6709\u6548\u5904\u7406\u5927\u6570\u636e\u96c6\u5e76\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97\u3002\u6b64\u5916\uff0c\u786e\u4fdd\u53ea\u8bfb\u53d6\u5fc5\u8981\u7684\u5217\u548c\u884c\uff0c\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\uff0c\u4e5f\u53ef\u4ee5\u63d0\u9ad8\u5904\u7406\u901f\u5ea6\u3002<\/p>\n<p><strong>\u5982\u4f55\u5904\u7406\u5408\u5e76\u540e\u53ef\u80fd\u51fa\u73b0\u7684\u6570\u636e\u5197\u4f59\u6216\u91cd\u590d\uff1f<\/strong><br \/>\u5728\u5408\u5e76\u56fe\u6591\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u6570\u636e\u5197\u4f59\u6216\u91cd\u590d\u7684\u60c5\u51b5\u3002\u53ef\u4ee5\u4f7f\u7528Geopandas\u7684<code>drop_duplicates()<\/code>\u65b9\u6cd5\u53bb\u9664\u91cd\u590d\u7684\u884c\u3002\u5982\u679c\u9700\u8981\u6839\u636e\u7279\u5b9a\u7684\u5c5e\u6027\u8fdb\u884c\u5408\u5e76\uff0c\u5219\u53ef\u4ee5\u4f7f\u7528<code>groupby()<\/code>\u529f\u80fd\uff0c\u7ed3\u5408<code>agg()<\/code>\u51fd\u6570\u6765\u8fdb\u884c\u6570\u636e\u6c47\u603b\uff0c\u4ece\u800c\u786e\u4fdd\u6bcf\u4e2a\u56fe\u6591\u7684\u552f\u4e00\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5982\u4f55\u628a\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76 \u4f7f\u7528Python\u5c06\u51e0\u4e07\u4e2a\u56fe\u6591\u5408\u5e76\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff1a\u4f7f\u7528Shapel [&hellip;]","protected":false},"author":3,"featured_media":1127327,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1127319"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1127319"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1127319\/revisions"}],"predecessor-version":[{"id":1127329,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1127319\/revisions\/1127329"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1127327"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1127319"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1127319"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1127319"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}