I am using Python 3.6.9 (7.3.1+dfsg-4, Apr 22 2020, 05:15:29) [PyPy 7.3.1 with GCC 9.3.0] in my Xubuntu. I need to install pandas library. I have already successfully installed numpy. But when I try pypy3 -m pip install pandas I got a long error:
---------------------------------------- ERROR: Failed cleaning build dir for numpy Failed to build numpy Installing collected packages: wheel, setuptools, numpy, Cython Running setup.py install for numpy: started Running setup.py install for numpy: finished with status 'error' ERROR: Command errored out with exit status 1: command: /usr/bin/pypy3 -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-gpher0s_/numpy_9f2456ae65fe40749181bd0050e0570b/setup.py'"'"'; __file__='"'"'/tmp/pip-install-gpher0s_/numpy_9f2456ae65fe40749181bd0050e0570b/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-0ftvn40b/install-record.txt --single-version-externally-managed --prefix /tmp/pip-build-env-8dqfm6qw/overlay --compile --install-headers /tmp/pip-build-env-8dqfm6qw/overlay/include/numpy cwd: /tmp/pip-install-gpher0s_/numpy_9f2456ae65fe40749181bd0050e0570b/ Complete output (358 lines): Running from numpy source directory. Note: if you need reliable uninstall behavior, then install with pip instead of using `setup.py install`: - `pip install .` (from a git repo or downloaded source release) - `pip install numpy` (last NumPy release on PyPi) blas_opt_info: blas_mkl_info: customize UnixCCompiler libraries mkl_rt not found in ['/usr/local/lib', '/usr/lib64', '/usr/lib', '/usr/lib/x86_64-linux-gnu'] NOT AVAILABLE blis_info: customize UnixCCompiler libraries blis not found in ['/usr/local/lib', '/usr/lib64', '/usr/lib', '/usr/lib/x86_64-linux-gnu'] NOT AVAILABLECan you help me how to install pandas in PYPY3, please?
4 Reset to default
