I made a dtype that is: mytype = np.dtype([(\'a\',np.uint8), (\'b\',np.uint8), (\'c\',np.uint8)]) so the array using this dtype:
I have a Numpy rec array from which I would like to do some quick queries similar to SQL: SELECT * where array[\'phase\'] == \"P\". I would like to get a Record Array as output with each row correspon
Is there a graceful way of handling None values in a conversion of a list of tuples to a numpy recarray using the single call to np.rec.fromrecords?Assuming I know what I want the missing value to be
I have a fairly simple question about how to sort an entire array/recarray by a given column.For example, given the array:
I\'m pretty new to numpy, and I\'m trying to replace a value in a recarray. So I have this array: import numpy as np
The answer will be very obvious I think, but I don\'t see it at the moment. How can I convert a record array back to a regular ndarray?
Just would like to get a quick idea on the best, meaning least coding, way to get lots of data in recarray into postgres using psycopg2. I have seen some stuff using cast but really I thought it would
I have mask record like this In [41]: x Out[41]: masked_records( CHR : [12 12 12 ..., 12 12 12] SNP : [rs4980929 rs4980929 rs49开发者_C百科80929 ..., rs7975069 rs7975069 rs7975069]
There seems to be a problem with the join_by function in numpy.lib开发者_C百科.recfunctions when doing an outer join on multiple keys.The matplotlib.mlab function works correctly.The recfunctions vers
I am trying to learn how to use numpy\'s structured arrays. Specifically, I was trying to add information to more than one field at a time. I tried:
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