ValueError: numpy.dtype has the wrong size, try recompiling ValueError: numpy.dtype has the wrong size, try recompiling pandas pandas

ValueError: numpy.dtype has the wrong size, try recompiling


(to expand a bit on my comment)

Numpy developers follow in general a policy of keeping a backward compatible binary interface (ABI). However, the ABI is not forward compatible.

What that means:

A package, that uses numpy in a compiled extension, is compiled against a specific version of numpy. Future version of numpy will be compatible with the compiled extension of the package (for exception see below).Distributers of those other packages do not need to recompile their package against a newer versions of numpy and users do not need to update these other packages, when users update to a newer version of numpy.

However, this does not go in the other direction. If a package is compiled against a specific numpy version, say 1.7, then there is no guarantee that the binaries of that package will work with older numpy versions, say 1.6, and very often or most of the time they will not.

The binary distribution of packages like pandas and statsmodels, that are compiled against a recent version of numpy, will not work when an older version of numpy is installed.Some packages, for example matplotlib, if I remember correctly, compile their extensions against the oldest numpy version that they support. In this case, users with the same old or any more recent version of numpy can use those binaries.

The error message in the question is a typical result of binary incompatibilities.

The solution is to get a binary compatible version, either by updating numpy to at least the version against which pandas or statsmodels were compiled, or to recompile pandas and statsmodels against the older version of numpy that is already installed.

Breaking the ABI backward compatibility:

Sometimes improvements or refactorings in numpy break ABI backward compatibility. This happened (unintentionally) with numpy 1.4.0.As a consequence, users that updated numpy to 1.4.0, had binary incompatibilities with all other compiled packages, that were compiled against a previous version of numpy. This requires that all packages with binary extensions that use numpy have to be recompiled to work with the ABI incompatible version.


For me (Mac OS X Maverics, Python 2.7)

easy_install --upgrade numpy

helped. After this you can install up-to-date packages pandas, scikit-learn, e.t.c. using pip:

pip install pandas


I found it to be a simple version being outdated or mismatch and was fixed with:

pip install --upgrade numpypip install --upgrade scipypip install --upgrade pandas

Or might work with the one liner:

pip install --upgrade numpy scipy pandas