geopandas can read almost any vector-based spatial data format including ESRI shapefile, GeoJSON files and more using the command:

geopandas 可以使用以下命令读取几乎任何基于矢量的空间数据格式，包括 ESRI shapefile、GeoJSON 文件等：

geopandas.read_file()

which returns a GeoDataFrame object. This is possible because geopandas makes use of the great fiona library, which in turn makes use of a massive open-source program called GDAL/OGR designed to facilitate spatial data transformations.

上述命令返回一个 GeoDataFrame 对象。上述命令的实现是因为 geopandas 使用了很棒的 fiona 库，而 fiona 库又使用了一个旨在促进空间数据转换的名为 GDAL/OGR 的大型开源程序。

Any arguments passed to geopandas.read_file() after the file name will be passed directly to fiona.open(), which does the actual data importation. In general, geopandas.read_file() is pretty smart and should do what you want without extra arguments, but for more help, type:

在文件名之后传递给geopandas.read_file()的任何参数都会直接传递给fiona.open()，后者会进行实际的数据导入。总的来说，geopandas.read_file() 非常有效，无需额外参数就可以做你想做的事，如要获得更多帮助，请输入：

import fiona; help(fiona.open)

Among other things, one can explicitly set the driver (shapefile, GeoJSON) with the driver keyword, or pick a single layer from a multi-layered file with the layer keyword:

除此之外，可以使用 driver 关键字显式设置驱动程序（shapefile、GeoJSON），或者使用 layer 关键字从多层文件中选择一个图层：

countries_gdf = geopandas.read_file("package.gpkg", layer='countries')

Currently fiona only exposes the default drivers. To display those, type:

目前fiona只公开了默认的驱动程序。要显示这些，请键入。

import fiona; fiona.supported_drivers

There is an array of unexposed but supported (depending on the GDAL-build) drivers. One can activate these on runtime by updating the supported_drivers dictionary like:

有一系列未公开但受支持（取决于 GDAL 构建）的驱动程序。可以通过更新 supported_drivers 字典在运行时激活它们，例如：

fiona.supported_drivers["NAS"] = "raw"

Where supported in fiona, geopandas can also load resources directly from a web URL, for example for GeoJSON files from geojson.xyz:

在 fiona 支持的情况下，geopandas 还可以直接从 web URL 加载资源，例如来自 geojson.xyz 的 GeoJSON 文件：

url = "http://d2ad6b4ur7yvpq.cloudfront.net/naturalearth-3.3.0/ne_110m_land.geojson"
df = geopandas.read_file(url)

You can also load ZIP files that contain your data:

您还可以加载包含数据的 ZIP 文件：

zipfile = "zip:///Users/name/Downloads/cb_2017_us_state_500k.zip"
states = geopandas.read_file(zipfile)

If the dataset is in a folder in the ZIP file, you have to append its name:

如果数据集位于 ZIP 文件的文件夹中，则必须附加其名称：

zipfile = "zip:///Users/name/Downloads/gadm36_AFG_shp.zip!data"

If there are multiple datasets in a folder in the ZIP file, you also have to specify the filename:

如果 ZIP 文件中的一个文件夹中有多个数据集，您还必须指定文件名：

zipfile = "zip:///Users/name/Downloads/gadm36_AFG_shp.zip!data/gadm36_AFG_1.shp"

It is also possible to read any file-like objects with a os.read() method, such as a file handler (e.g. via built-in open() function) or StringIO:

也可以使用 os.read() 方法读取任何类似文件的对象，例如文件处理程序（例如通过内置的 open() 函数）或 StringIO：

filename = "test.geojson"
file = open(filename)
df = geopandas.read_file(file)

File-like objects from fsspec can also be used to read data, allowing for any combination of storage backends and caching supported by that project:

fsspec 中的类文件对象也可用于读取数据，允许该项目支持的存储后端和缓存的任意组合：

path = "simplecache::http://download.geofabrik.de/antarctica-latest-free.shp.zip"
with fsspec.open(path) as file:
    df = geopandas.read_file(file)

You can also read path objects:

您还可以读取路径对象：

import pathlib
path_object = pathlib.path(filename)
df = geopandas.read_file(path_object)

Reading subsets of the data

Since geopandas is powered by Fiona, which is powered by GDAL, you can take advantage of pre-filtering when loading in larger datasets. This can be done geospatially with a geometry or bounding box. You can also filter rows loaded with a slice. Read more at geopandas.read_file().

由于 geopandas 由 Fiona 提供支持，而 Fiona 由 GDAL 提供支持，因此您可以在加载更大的数据集时利用预过滤。这可以通过几何或边界框在地理空间上完成。还可以过滤加载了切片的行。在 geopandas.read_file() 中阅读更多内容。

Geometry Filter

The geometry filter only loads data that intersects with the geometry.

只加载与几何对象相交的数据。

gdf_mask = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres")
)
gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_cities"),
    mask=gdf_mask[gdf_mask.continent=="Africa"],
)

Bounding Box Filter

The bounding box filter only loads data that intersects with the bounding box.

仅加载与边界框相交的数据。

bbox = (
    1031051.7879884212, 224272.49231459625, 1047224.3104931959, 244317.30894023244
)
gdf = geopandas.read_file(
    geopandas.datasets.get_path("nybb"),
    bbox=bbox,
)

Row Filter

Filter the rows loaded in from the file using an integer (for the first n rows) or a slice object.

使用整数（对于前 n 行）或切片对象过滤从文件加载的行。

gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    rows=10,
)
gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    rows=slice(10, 20),
)

Field/Column Filters

Load in a subset of fields from the file:

从文件中加载字段的子集：

Note：Requires Fiona 1.9+

gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    include_fields=["pop_est", "continent", "name"],
)

Note：Requires Fiona 1.8+

gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    ignore_fields=["iso_a3", "gdp_md_est"],
)

Skip loading geometry from the file:

从文件中加载时跳过活动几何列“geometry”列【geometry】

Note：Requires Fiona 1.8+

Note：Returns pandas.DataFrame

返回pandas.DataFrame类型

pdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    ignore_geometry=True,
)

SQL WHERE Filter

Load in a subset of data with a SQL WHERE clause.

使用 SQL WHERE 子句加载数据子集

Note：Requires Fiona 1.9+ or the pyogrio engine.

gdf = geopandas.read_file(
    geopandas.datasets.get_path("naturalearth_lowres"),
    where="continent='Africa'",
)

标签 GeoPandas, Python, Python-GIS