Difference between revisions of "Python/Miscellaneous Snippets and Tips"
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Here are miscellaneous tips and tricks when working with Python files. | Here are miscellaneous tips and tricks when working with Python files. | ||
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== Write Data to Text File (ie. CSV) == | == Write Data to Text File (ie. CSV) == |
Revision as of 11:18, 9 August 2021
Here are miscellaneous tips and tricks when working with Python files.
Write Data to Text File (ie. CSV)
Given data in some Python object (most likely a numpy-derived array, but possibly just a normal Python list), how do you write it out to a file? Use numpy.savetxt
(or more likely np.savetxt
).
Example: Given a array, A
, of shape [n, m]
, simply use
np.savetxt('path/file.dat', A)
which creates a file with n
rows and m
columns.
Numpy's documentation has information on other useful arguments to change numerical formats, separators, and adding headers to the file.
Write multiple 1D arrays as columns
To do this, use numpy.column_stack
to create an array with the columns "stacked" together.
Example: Given two 1D arrays, a
and b
, of the same size, use:
np.savetxt('path/file.dat', np.column_stack((a,b)) )
Two things to note here:
-
np.column_stack
takes a list or tuple as an argument, hence the two sets of((...))
. -
np.column_stack
creates an entirely new array and copies the given data into it. As such, it will double the total amount of memory used; once for the original 1D arrays, and again for the brand new array storing a copy of the original data.