How to read GDB layer name in geopandas?

How to read GDB layer name in geopandas?

I have a list of layers an I want to import them to geopandas and have their object name to be the same as the layer name. In this case layer = gpd.read_file (…) should be the name of the actual layer from the layerlist. layerlist = fiona.listlayers (gdb) for layer in layerlist: layer = gpd.read_file (gdb, driver=”FileGDB”, layer=layer)

Is it possible to read files in geopandas?

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

How to export a geodataframe to a file?

GeoDataFrames can be exported to many different standard formats using the geopandas.GeoDataFrame.to_file() method. For a full list of supported formats, type import fiona; fiona.supported_drivers . In addition, GeoDataFrames can be uploaded to PostGIS database (starting with GeoPandas 0.8) by using the geopandas.GeoDataFrame.to_postgis() method.

Where are tuples stored in the geodataframe?

For example tuples or lists can be easily stored in the GeoDataFrame, but saving them to e.g. GeoPackage or Shapefile will raise a ValueError. Before saving to a file, they need to be converted to a format supported by a selected driver.

Is it possible to read files from geopandas?

As indicated by @littlexsparkee, geopandas can now read known file formats directly from url’s (this is possible since version 0.4), e.g.: Since Geopandas 0.8 it is also possible to directly read filelike objects.

How to convert a CSV to a geopandas Dataframe?

I want to convert it to a geopandas dataframe. TypeError: Input must be valid geometry objects: MULTIPOLYGON ( ( (-73.97604935657381 40.631275905646774, -73.97716511994669 40.63074665412933,…. For some reason geopandas seems to be unable to convert a geometry column from a pandas dataframe.

Is there a fiona.bytescollection solution for TopoJSON?

Since fiona.BytesCollection doesn’t seem to work for TopoJSON here an solution that works for all without the need of gdal:

Is it possible to read geodatabase from S3?

The geodatabase file is on S3, so I’m using fssspec to read it in, but I’m getting an error: it works to read in a geojson file: Here’s the error traceback:

What are the two main data structures in geopandas?

GeoPandas implements two main data structures, a GeoSeries and a GeoDataFrame. These are subclasses of pandas Series and DataFrame, respectively. A GeoSeries is essentially a vector where each entry in the vector is a set of shapes corresponding to one observation.

Which is the default setting for pygeos in geopandas?

By default (None), it tries to infer and use 3 decimals for projected coordinates and 5 decimals for geographic coordinates. use_pygeos: True [default: True] Whether to use PyGEOS to speed up spatial operations. The default is True if PyGEOS is installed, and follows the USE_PYGEOS environment variable if set.

Where do I find the geodatabase in GDAL?

The contents of the file geodatabase will appear in the Layers pane, and each layer can be exported to any other format with write support in GDAL, including the shapefile format.

Where do I find the geodatabase in QGIS?

The geodatabase may appear as a folder and may not be selectable using the Add Vector Layer tool in QGIS. The contents of the file geodatabase will appear in the Layers pane, and each layer can be exported to any other format with write support in GDAL, including the shapefile format.

Why do we use the file geodatabase format?

The file geodatabase format has emerged as a very common format for storing and exchanging spatial data, particularly considering that it allows for the storage of multiple data layers, and that it allows for the storage of data layers that exceed the limits of other specifications.