This error raised while installing geopandas. I've looking for its solution on the web, but none of them really explain what happened and how to solve it..
This is the full error:
Collecting geopandas
Using cached https://files.pythonhosted.org/packages/24/11/d77c157c16909bd77557d00798b05a5b6615ed60acb5900fbe6a65d35e93/geopandas-0.4.0-py2.py3-none-any.whl
Requirement already satisfied: shapely in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (1.6.4.post2)
Requirement already satisfied: pandas in c:\users\alvaro\anaconda3\envs\tfdeeplearning\lib\site-packages (from geopandas) (0.20.3)
Collecting fiona (from geopandas)
Using cached https://files.pythonhosted.org/packages/3a/16/84960540e9fce61d767fd2f0f1d95f4c63e99ab5d8fddc308e8b51b059b8/Fiona-1.8.4.tar.gz
Complete output from command python setup.py egg_info:
A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\Alvaro\AppData\Local\Temp\pip-install-oxgkjg8l\fiona\
pip install wheel
pip install pipwin
pipwin install numpy
pipwin install pandas
pipwin install shapely
pipwin install gdal
pipwin install fiona
pipwin install pyproj
pipwin install six
pipwin install rtree
pipwin install geopandas
here are the source links:
http://geopandas.org/install.html#installation
https://pip.pypa.io/en/latest/user_guide/#installing-from-wheels
https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy
If you still have problems, consider uninstalling the above (pip uninstall) and reinstalling.
I solved this problem by running the following commands:
pip install pipwin
pipwin install gdal
pipwin install fiona
pip install geopandas
Works successfully on Windows.
Geospatial Data Abstraction Library (GDAL) is a library designed for vector geospatial data formats. It's a prerequisite for installing Fiona, the Python API for OGR (which doesn't really stand for anything), which is in turn a prerequisite for Geopandas. On UNIX-like systems the gdal-config script tells Fiona stuff about your particular gdal installation.
It seems that your gdal-config is not in one of the usual places on your PATH, so Fiona was unable to find it.
If you're using Anaconda, best is to remove gdal with conda remove gdal and then do a fresh conda install geopandas.
As a general rule, if you're using Conda you should never use pip to install something inside it unless you're absolutely sure conda offers no support for it. (Many package can be found on conda by specifying the right channel - -c argument.) And specifically in the case of geopandas, the maintainers recommend using conda over pip, since pip requires you to install the dependencies correctly.
I had a lot of issues myself installing geopandas, mostly showing error when downloading fiona and gdal. I did every step above and did a conda install geopandas but failed. The only thing worked for me is to install fiona and gdal wheel separately.
go to the link by Christoph: gohlke:https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
You can search for fiona and gdal wheel files. Make sure you choose the file as per your python version, if it is 3.7 then there would be cp37.
Download the file
go to command prompt, put cd and then pip install , install GDAL wheel file, then fiona, then just do pip install geopandas.
This solution worked for me.
To install gdal, I followed the following steps:
downloaded the version that satisfies my computer (64 bit) from
https://www.lfd.uci.edu/~gohlke/pythonlibs/ . The file was GDAL-3.1.4-cp37-cp37m-win_amd64.whl
Put the file in a folder on the desktop.
From cmd, i moved to that directory and executed python -m pip install GDAL-3.1.4-cp37-cp37m-win_amd64.whl
This is followed by installing fiona the same way: python -m pip install Fiona-1.8.18-cp37-cp37m-win_amd64.whl
For shapely, i executed conda install -c conda-forge shapely
After that, i was able to install keplergl as usual: pip install keplergl
install descartes: conda install -c conda-forge descartes (or python -m pip install descartes).
In this way, i didn't have to play around with the 'Environmental Variables' as this may affect other programs
Cheers..
Installing geopandas
Geopandas has very complex multi-language dependencies, some of which need to be built with consistent compiler versions across packages. Because of this, the geopandas docs recommend installing using conda in a new environment using conda-forge only. Here are some general best practices to keep in mind:
conda is the recommended installation method. You can install geopandas from pip or source, but it's going to be a bumpy ride and it's not recommended. If you're installing conda for the first time, I recommend you start with miniconda (or better yet miniforge, a conda-forge-first miniconda variant), not anaconda, to keep your base env lean.
When using conda, you should not mix and match conda channels.
When installing geopandas, try creating a fresh environment rather than installing into your base environment. If you have anaconda installed, it comes with a large number of packages from the "defaults" channel installed in your base environment. I recommend deleting anaconda and installing miniconda, then installing into a new environment.
Try to create a new environment with everything you plan to use all at once rather than iteratively modifying the environment. In other words, if you want to use geopandas with scikit_learn, folium, and rasterio, install them together with a single conda create command
As a last resort, delete your conda installation and re-install miniconda. Desperate times call for desperate measures, and this usually resolves gnarly installation nightmares.
To create a fresh conda environment in which you install all necessary dependencies at the same time, using the conda-forge channel:
conda create -n my-geopandas-env -c conda-forge geopandas [all other packages you need]
For example, I might set up an environment with something along the lines of...
conda create -n my-geopandas-env -c conda-forge python=3.9 \
ipython ipykernel geopandas scipy seaborn fiona matplotlib cartopy
Bundling your installations into a single environment creation step like this reduces the chance of packages falling out of sync. To speed this process up, you could first install mamba or mambaforge, a faster drop-in replacement for conda, into your base environment and then run the above commands with mamba instead of conda.
Generally, it's best to avoid installing much of anything in your base environment (cross-environment system utilities like mamba are some of the few exceptions). If you already have a complex base environment (maybe you started with anaconda rather than miniconda) this may be the time to delete your entire conda installation and start from scratch (I know that's terrifying... sorry! but it'll save you heartache in the future). mamba is great for speeding this process up.
Connecting your editor to the conda environment
Once you have installed all of the packages you need, activate your environment with conda activate my-geopandas-env. See the conda guide to managing environments for more info.
Jupyter/ipython
Some editors/IDEs including jupyter require additional packages - jupyter requires that ipython and ipykernel be installed in order to load the environment within the notebook or editor - that's why I included ipykernel in my list above. See the ipykernel docs for more info.
Other IDES
To link this environment to an IDE such as VSCODE, spider, etc., find the location of this python version with conda run -n my-geopandas-env which python then point your editor to this python executable. Check the docs of your specific editor to get more targeted info about how to set up a conda environment for use with your editor:
Spider: FAQ on using an existing environment and Spider wiki guide to working with packages and environments
VSCode: Using python environments in vscode
PyCharm: Configure a conda virtual environment
I don't have conda installed, then using just pip I followed these steps:
Download GDAL and Fiona wheels directly on:
GDAL: https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
FIONA: https://www.lfd.uci.edu/~gohlke/pythonlibs/#fiona
Then:
pip install <gdal.whl>
pip install <fiona.whl>
In my case I did pip install GDAL-3.4.1-cp38-cp38-win_amd64.whl and Fiona-1.8.21-cp38-cp38-win_amd64.whl. Where cp38 stands for python 3.8.
After that you are able to install geopandas with pip as well.
pip install geo pandas
For me, the only solution was to install the ready binaries from here
https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal
Then just install locally
pip install GDAL-3.1.4-cp38-cp38-win_amd64.whl
One way in which I could install geopandas was through the Anaconda Navigator. Get into the environment and install the package 'geopandas'. After that I could import the geopandas package in spyder
I will add
!pip install descartes
to #JDOaktown list.
I started with pip install geopandas and got the error, but later tried with conda install --channel conda-forge geopandas and the error disappeared.
Successfully installed in RHEL 7.8.
It automatically downloaded the required packages. This might be helpful
Installing collected packages: certifi, pyproj, shapely, attrs, click, click-plugins, munch, cligj, fiona, geopandas
Successfully installed attrs-20.3.0 certifi-2020.11.8 click-7.1.2 click-plugins-1.1.1 cligj-0.7.0 fiona-1.8.17 geopandas-0.8.1 munch-2.5.0 pyproj-3.0.0.post1 shapely-1.7.1
If you want to install GDAL, Geopandas, Shapely, Fiona etc in a windows Virtual Environment download .whl files for all of them and first install GDAL using
pip install gdal-.whl
Following this command edit the activate.bat file in you venv\Scripts folder and add
GDAL_CONFIG = \venv\Lib\site-packages\osgeo
Then you can install rest using pip install
I started off with a clean environment gdal_test in Conda environments, but made the mistake of using the old activate gdal_test instead of conda activate gdal_test. This made Conda Environment resolving take forever, which is why I resolved to other methods at first.
Takeaway: let conda handle it, with a proper new environment.
I ran into this problem not with anaconda/windows, but with python:3.6 Docker image. Google search always led me to this question, so I think I will share how I resolve my issue in case others also end up here.
Based on here, you need to install system relevant packages in the Dockerfile before running pip install geopandas or pip install requirements.txt:
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
libatlas-base-dev \
libgdal-dev \
gfortran
The following worked on macOS:
brew install gdal --HEAD
Verify the installation by running gdal-config --version
Following that pip installation as normal worked without a problem.
While trying to install a particular package using conda, I didn't notice how many packages were going to be downgraded and foolishly gave the go-ahead. For the most part, the version numbers weren't downgraded, but they downgraded from a py37 build channel to a py27 build channel. Running conda list now gives me lines with a mix of py27 and py37:
jupyter 1.0.0 py37_7
jupyter_client 5.2.4 py27_0
jupyter_console 5.2.0 py27_1
jupyter_core 4.4.0 py27_0
jupyterlab 0.35.3 py37_0
I can't remember what it looked like before, but I don't believe I had this garbled mess of python2 and python3, as I haven't built anything with python2 into my conda. Running conda update --all doesn't resolve this, as I believe it only checks the version and not the build path. How can I change everything back to python3 and ideally remove all traces of python2?
Edit:
The line in particular that caused this was conda install -c menpo vtk=7 when trying to install DAETools
I think the easiest way to fix this should be to explicitly install python=3, i.e.:
conda install python=3
possibly this will want to remove vtk again, but when I specified python=3, I got a version of vtk=7 build with python 3.5 from the same channel you used, i.e. there is a python 3 version available.
It's also possible to revert your anaconda distribution back to 'factory settings' by executing conda update conda, followed by conda install anaconda. Afterwards all your package versions should be the same as the ones that you would have after a fresh installation of the (latest) full Anaconda distribution.
I used pip to install the Resource module to the default conda environment on my laptop: (C:\Users\my_username\Anaconda2). I think it is called root. I installed pip to the conda environment and so I'm 90% sure the resource was installed within the environment. And indeed running conda list shows that the package is listed within the environment. Here is a section of the output:
# packages in environment at C:\Users\conna\Anaconda2:
#
qtpy 1.2.1 py27_0
requests 2.14.2 py27_0
Resource 0.2.0 <pip>
rope 0.9.4 py27_1
ruamel_yaml 0.11.14 py27_1
scandir 1.5 py27_0
scikit-image 0.13.0 np112py27_0
However when I run
conda update Resource
I get the following error:
PackageNotInstalledError: Package is not installed in prefix.
prefix: C:\Users\conna\Anaconda2
package name: Resource
How is it possible that conda list shows the module is present but conda update can't see them? I also noticed that conda update doesn't recognize any packages with <pip>. What is happening?
conda only manages the packages that are installed using a conda command. If you installed a package with pip (or using python setup.py install or develop) it will show up with conda list (because that shows all packages no matter how they were installed) but conda won't manage that package. Simply because it doesn't know how!
So if you installed a package with pip you also need to upgrade/update it with pip:
pip install [package_name] --upgrade
Try this;
pip install Resource --upgrade
I'm working with python 3.4. I use anaconda to install my data-science's packages and I need the statsmodels 0.8 :
https://pypi.python.org/pypi/statsmodels/
but on anaconda there is only the statsmodels 0.6 :
https://docs.continuum.io/anaconda/pkg-docs
And I really need to work with conda for the deployment.
Any idea of how can I have the 0.8 ?
IF a package is available on PyPi, you can use
conda skeleton pypi package
to create a condo-recipe for that package, then
conda build package
conda install --use-local package
to build and install the package
I am trying to upgrade package of scikit-learn from 0.16 to 0.17. For that I am trying to use binaries from this website: http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn. I have Windows 7 x64 bit. I downloaded the relevant package locally and gave following commands and got Requirement already up-to-date:
C:\Users\skumar>pip install --upgrade --use-wheel --no-index --find-links=../../
SOURCE/APPS scikit-learn
Ignoring indexes: https://pypi.python.org/simple
Requirement already up-to-date: scikit-learn in c:\anaconda3\lib\site-packages
Then I tried to upgrade it from remote site and got similar result:
C:\Users\skumar>pip install --upgrade --use-wheel --no-index --trusted-host www.
lfd.uci.edu --find-links=http://www.lfd.uci.edu/~gohlke/pythonlibs/ scikit-learn
Ignoring indexes: https://pypi.python.org/simple
Requirement already up-to-date: scikit-learn in c:\anaconda3\lib\site-packages
On Remote site there are two versions i.e., 0.16 & 0.17. Is there a way to specify version in command? Or how do you install/upgrade wheel file?
Anaconda comes with the conda package manager which is designed to handle these kinds of upgrades. Start by updating conda itself to get the most recent package lists:
conda update conda
And then install the version of scikit-learn you want
conda install scikit-learn=0.17
All necessary dependencies will be upgraded as well. If you have trouble with conda on Windows, there are some relevant FAQ here: http://docs.continuum.io/anaconda/faq
Following Worked for me for scikit-learn on Anaconda-Jupyter Notebook.
Upgrading my scikit-learn from 0.19.1 to 0.19.2 in anaconda installed on Ubuntu on Google VM instance:
Run the following commands in the terminal:
First, check existing available packages with versions by using:
conda list
It will show different packages and their installed versions in the output. Here check for scikit-learn. e.g. for me, the output was:
scikit-learn 0.19.1 py36hedc7406_0
Now I want to Upgrade to 0.19.2 July 2018 release i.e. latest available version.
conda config --append channels conda-forge
conda install scikit-learn=0.19.2
As you are trying to upgrade to 0.17 version try the following command:
conda install scikit-learn=0.17
Now check the required version of the scikit-learn is installed correctly or not by using:
conda list
For me the Output was:
scikit-learn 0.19.2 py36_blas_openblasha84fab4_201 [blas_openblas] conda-forge
Note: Don't use pip command if you are using Anaconda or Miniconda
I tried following commands:
!conda update conda
!pip install -U scikit-learn
It will install the required packages also will show in the conda list but if you try to import that package it will not work.
On the website http://scikit-learn.org/stable/install.html it is mentioned as:
Warning To upgrade or uninstall scikit-learn installed with Anaconda or conda you should not use the pip.
So to upgrade scikit-learn package, you have to follow below process
Step-1: Open your terminal(Ctrl+Alt+t)
Step-2: Now for checking currently installed packages along with the
versions installed on your
conda environment by typing conda list
Step-3: Now for upgrade type below command
conda update scikit-learn
Hope it helps!!
I would suggest using conda. Conda is an anconda specific package manager. If you want to know more about conda, read the conda docs.
Using conda in the command line, the command below would install scipy 0.17.
conda install scipy=0.17.0
Updating a Specific Library - scikit-learn:
Anaconda (conda):
conda install scikit-learn
Pip Installs Packages (pip):
pip install --upgrade scikit-learn
Verify Update:
conda list scikit-learn
It should now display the current (and desired) version of the scikit-learn library.
For me personally, I tried using the conda command to update the scikit-learn library and it acted as if it were installing the latest version to then later discover (with an execution of the conda list scikit-learn command) that it was the same version as previously and never updated (or recognized the update?). When I used the pip command, it worked like a charm and correctly updated the scikit-learn library to the latest version!
Hope this helps!
More in-depth details of latest version can be found here (be mindful this applies to the scikit-learn library version of 0.22):
Release Highlights for scikit-learn 0.22
I made it work to update to 0.24.1, on Windows 10 64bits, so I share the way I did it with the GUI:
launch Anaconda3 gui
on the left menu, click "environments"
next to "base (root)", click on the green arrow/triangle
select "Open Terminal"
type the command line:
conda install scikit-learn==0.24.1
It worked without error.
If you are using Jupyter in anaconda, after conda update scikit-learn in terminal, close anaconda and restart, otherwise the error will occur again.