GeoPandas from source: See the section on conda above for more details on py-opencv-4.0.1 | 1.9 MB | ################################################# | 100% retrying with flexible solveerror while installing the packages and managing the dependencies. Starting with GeoPandas 0.8, it is possible to optionally use those -> llvmdev==5.0.0 -> llvm-meta=5.0.0 Retrying with flexible solve. libopencv anaconda/win-64::libopencv-4.0.1-hbb9e17c_0 In my case the problem was also solved by downgrading. -> llvmdev==5.0.0 I had the same problem doing Resolved by first creating an environment conda create -n kedro then activating it conda activate kedro. Why do men's bikes have high bars where you can hit your testicles while women's bikes have the bar much lower? scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] I finally did the standard download: conda install -c conda-forge opencv And it worked! Paste that into your Terminal in your newly-made conda environment and hit Enter. privacy statement. Making statements based on opinion; back them up with references or personal experience. Srinivas Ramakrishna is a Solution Architect and has 14+ Years of Experience in the Software Industry. pytest-astropy -> pytest-arraydiff[version='>=0.1'] -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] I retried conda install -c conda-forge kedro and it worked. If you would like to change your settings or withdraw consent at any time, the link to do so is in our privacy policy accessible from our home page.. What solved it for me was a silly small mistake. I finally did the standard download: conda install -c conda-forge opencv, It stopped to give error messages an in Anaconda prompty I can do installing conda install -c districtdatalabs yellowbrick, However, it is not working in Jupyter notebook, when I retry to install yellowbrick, it says that it is already installed. This is a much safer way imo is to tell conda to have a look on the same package published in other channels should the default channel one is having unsolvable dependencies. scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? is there such a thing as "right to be heard"? as well: When using pip to install GeoPandas, you need to make sure that all dependencies are An example of data being processed may be a unique identifier stored in a cookie. pytables -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] vs2015_runtime anaconda/win-64::vs2015_runtime-14.16.27012-hf0eaf9b_0 Retrying with flexible solve." or conda-forge channel may be better for your needs (e.g. provided by Anaconda. xz anaconda/win-64::xz-5.2.4-h2fa13f4_4 setuptools anaconda/win-64::setuptools-42.0.2-py38_0 h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] You need to make sure that they are properly installed. h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] Got it to install by rolling conda back to 4.6.14 from 4.8.0. pytest-doctestplus -> numpy[version='>=1.10'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] statsmodels -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] This x100. seems like less headaches. Sign up for a free GitHub account to open an issue and contact its maintainers and the community.