I am trying to install the geopandas
package with Anaconda Prompt, but after I use conda install geopandas
an unexpected thing happened:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages
After this, it proceeds to search for conflicts, but hours pass without finishing. In the end, I still cannot use geopandas
.
I have also tried installing geopandas
in a different virtual environment and it works but I do not know how to use the environment in Jupyter Notebooks.
I would like to know, how can install geopandas
without a separate environment?
Or, alternatively, how can I use geopandas
in Jupyter Notebooks after install it in a separate environment?
Here is a novel procedure to install successfully the Geopandas library when working with Anaconda in Windows. Download Fiona, Pyproj, Shapely, GDAL and Geopandas wheels from: Install wheels manually with pip on Anaconda Prompt as follows: On the following order: GDAL, Pyproj, Fiona, Shapely and Geopandas
I'm currently working with Python 3.7.6 with Anaconda and Jupyter Notebook. I used to work with geopandas like 1 week ago with no problems. Then I tried to install osmnx and it took forever, more than 10 hours, so I interrupted it.
This can be obtained by installing the Anaconda Distribution (a free Python distribution for data science), or through miniconda (minimal distribution only containing Python and the conda package manager). See also the installation docs for more information on how to install Anaconda or miniconda locally.
GeoPandas depends for its spatial functionality on a large geospatial, open source stack of libraries ( GEOS, GDAL, PROJ ). See the Dependencies section below for more details. Those base C libraries can sometimes be a challenge to install. Therefore, we advise you to closely follow the recommendations below to avoid installation problems.
Install it in a new env, and include ipykernel
if you plan to use it in Jupyter:
conda create -n my_env geopandas ipykernel
Note, nb_conda_kernels
should be installed install in your base env (i.e. where you launch Jupyter from). This enables Jupyter to automatically recognize other envs that are kernel-ready:
conda install -n base nb_conda_kernels
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