I am trying to set up an environment with python 3.7, pandas and scikit-learn to test if my code is compatible with 3.7. But I am having a hard time making sense of the error messages I run into. I am working on Windows 10 64-bit
When I run
conda create --name Py37Test python=3.7 pandas scikit-learn
I get this error message
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- python=3.7
- scikit-learn -> python[version='>=2.7,<2.8.0a0']
Use "conda info <package>" to see the dependencies for each package.
but when I run
conda info scikit-learn
it says:
dependencies:
mkl >=2018.0.0
numpy >=1.11.3,<2.0a0
python >=3.6,<3.7.0a0
scipy
vc 14.*
Similarly, if I run
conda create --name Py37Test python=3.7 pandas
I get the error:
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- pandas -> python-dateutil -> six
- pandas -> python[version='>=2.7,<2.8.0a0']
- python=3.7
Use "conda info <package>" to see the dependencies for each package.
enter code here
And when I then run
conda info pandas
I get
dependencies:
numpy >=1.11.3,<2.0a0
python >=3.6,<3.7.0a0
python-dateutil >=2.5.*
pytz
vc 14.*
Which again seems to imply that dependencies are OK.
Help?!
Update: Running
>conda create --name Py37Test python=3.7 pandas=0.23.1 scikit-learn=0.19.1
gives:
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- python=3.7
- scikit-learn=0.19.1 -> python[version='>=2.7,<2.8.0a0']
Use "conda info <package>" to see the dependencies for each package.