Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas

Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) 1314 Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas

Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone toolkit, Release 0.15.1 Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas

Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas Returns indexer : ndarray Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) pandas

Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone

Numpy 1.7 and users should therefore use this experimental(!) feature with caution and at their own risk. To the extent that the datetime64 and busdaycalendar APIs in Numpy have to change to fix the timezone mask) : (ndarray, ndarray) Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer, mask = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer)

mask) : (ndarray, ndarray) Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer, mask = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) mask) : (ndarray, ndarray) Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer, mask = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer)

mask) : (ndarray, ndarray) Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer, mask = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer) mask) : (ndarray, ndarray) Notes This is a low-level method and probably should be used at your own risk Examples >>> indexer, mask = index.get_indexer(new_index) >>> new_values = cur_values.take(indexer)

Because XSLT is a programming language, use it with caution since such scripts can pose a security risk in your environment and can run large or infinite recursive operations. Always test scripts on small

Because XSLT is a programming language, use it with caution since such scripts can pose a security risk in your environment and can run large or infinite recursive operations. Always test scripts on small