code that was just checked out. There are two primary methods of doing this. 1. The best way to develop pandas is to build the C extensions in-place by running: python setup.py build_ext --inplace 3 will call the built C extensions 2. Another very common option is to do a develop install of pandas: python setup.py develop This makes a symbolic link that tells the Python interpreter to import pandas envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/

code that was just checked out. There are two primary methods of doing this. 1. The best way to develop pandas is to build the C extensions in-place by running: python setup.py build_ext --inplace 3 will call the built C extensions 2. Another very common option is to do a develop install of pandas: python setup.py develop This makes a symbolic link that tells the Python interpreter to import pandas envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/

code that was just checked out. There are two primary methods of doing this. 1. The best way to develop pandas is to build the C extensions in-place by running: python setup.py build_ext --inplace If very common option is to do a develop install of pandas: 3.3. Working with the code 381 pandas: powerful Python data analysis toolkit, Release 0.20.3 python setup.py develop This makes a symbolic link envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/

code that was just checked out. There are two primary methods of doing this. 1. The best way to develop pandas is to build the C extensions in-place by running: python setup.py build_ext --inplace If very common option is to do a develop install of pandas: 3.3. Working with the code 379 pandas: powerful Python data analysis toolkit, Release 0.20.2 python setup.py develop This makes a symbolic link envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/

code that was just checked out. There are two primary methods of doing this. 1. The best way to develop pandas is to build the C extensions in-place by running: python setup.py build_ext --inplace If analysis toolkit, Release 0.17.0 2. Another very common option is to do a develop install of pandas: python setup.py develop This makes a symbolic link that tells the Python interpreter to import pandas

envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/ for MyExtensionArray. A mixin class, ExtensionScalarOpsMixin supports this second approach. If develop- ing an ExtensionArray subclass, for example MyExtensionArray, can simply include ExtensionScalarOpsMixin

envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/ for MyExtensionArray. A mixin class, ExtensionScalarOpsMixin supports this second approach. If develop- ing an ExtensionArray subclass, for example MyExtensionArray, can simply include ExtensionScalarOpsMixin

envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/ for MyExtensionArray. A mixin class, ExtensionScalarOpsMixin supports this second approach. If develop- ing an ExtensionArray subclass, for example MyExtensionArray, can simply include ExtensionScalarOpsMixin

envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/ for MyExtensionArray. A mixin class, ExtensionScalarOpsMixin supports this second approach. If develop- ing an ExtensionArray subclass, for example MyExtensionArray, can simply include ExtensionScalarOpsMixin

envi- ronment. This can be useful if you do not have virtualenv or conda, or are using the setup.py develop ap- proach discussed above; for the in-place build you need to set PYTHONPATH, e.g. PYTHONPATH="$PWD/ for MyExtensionArray. A mixin class, ExtensionScalarOpsMixin supports this second approach. If develop- ing an ExtensionArray subclass, for example MyExtensionArray, can simply include ExtensionScalarOpsMixin