OWSLib | Python package for client programming | Dataset library
kandi X-RAY | OWSLib Summary
kandi X-RAY | OWSLib Summary
OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models.
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Top functions reviewed by kandi - BETA
- Get a single feature
- Format bbox parameter
- Get code URN
- Get the authority code
- Retrieve records from the server
- Return an operation by its name
- Add new namespaces to the root element
- Invoke the request
- Gets the WCS coverage for a given bounding box
- Retrieve feature information from the server
- Get an observation
- Generate the GML XML element
- Parse an XML variable
- Build the Metadata object
- Calls GetCoverage API
- Builds the Metadata object
- Request an observation
- Get feature information
- Construct a Csw30 transaction
- Get a feature
- Parse complex data element
- Performs a getmap operation
- Wrapper around getCoverage
- Wrapper for getCoverage
- Get a list of stored queries
- Performs a getMap operation
OWSLib Key Features
OWSLib Examples and Code Snippets
Community Discussions
Trending Discussions on OWSLib
QUESTION
I want to create a geopandas dataframe from a url using owslib:
...ANSWER
Answered 2020-Aug-14 at 11:26The "solution" was to uninstall Anaconda and install an older version (Anaconda3-2019.03)
then install packages:
- geopandas
- owslib
And update pyproj package
QUESTION
The shell command pip install cartopy
led to several errors.
At first, the following error occurred:
...ANSWER
Answered 2020-Aug-04 at 08:40After searching solutions to the main error message c++: error: unrecognized command line option '-R'
, I finally found it in this discussion.
What I did was searching for the relevant files using the mighty find
method:
QUESTION
I have a "seed" GeoDataFrame (GDF)(RED) which contains a 0.5 arc minutes global grid ((180*2)*(360*2) = 259200). Each cell contains an absolute population estimate. In addition, I have a "leech" GDF (GREEN) with roughly 8250 adjoining non-regular shapes of various sizes (watersheds).
I wrote a script to allocate the population estimates to the geometries in the leech GDF based on the overlapping area between grid cells (seed GDF) and the geometries in the leech GDF. The script works perfectly fine for my sample data (see below). However, once I run it on my actual data, it is very slow. I ran it overnight and the next morning only 27% of the calculations had been performed. I will have to run this script many times and waiting for two days each time, is simply not an option.
After doing a bit of literature research, I already replaced (?) for loops with for index i in df.iterrows()
(or is this the same as "conventional" python for loops) but it didn't bring about the performance imporvement I had hoped for.
Any suggestion son how I can speed up my code? In twelve hours, my script only processed only ~30000 rows out of ~200000.
My expected output is the column leech_df['leeched_values']
.
ANSWER
Answered 2020-Feb-27 at 18:33It might be worthy to profile your code in details to get precise insights of what is your bottleneck.
Bellow some advises to already improve your script performance:
- Avoid
list.append(1)
to count occurrences, usecollection.Counter
instead; - Avoid
pandas.DataFrame.iterrows
, usepandas.DataFrame.itertuples
instead; - Avoid extra assignation that are not needed, use
pandas.DataFrame.fillna
instead:
Eg. this line:
QUESTION
I am trying to make a WFS request and create a GeoDataFrame (from the geopandas library) with this data. However, when I run my code, an assert
raises an error:
ANSWER
Answered 2020-Jan-22 at 15:14You don't have a list with four elements, you have a string.
To solve this, split your string to create a list before the assert, like bb = bb.split(',')
.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install OWSLib
You can use OWSLib like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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