On 21/02/2019 13:49, Peter Otten wrote:
Robin Becker wrote:
.......
Isn't df.values a numpy array? Then try the more direct and likely more
efficient
df.values.tolist()
or, if you ever want to transpose
df.values.T.tolist()
The first seems to achieve what your sample code does. (In addition it also
converts the numpy type to the corresponding python builtin, i. e.
numpy.float64 becomes float etc.)
Thanks for the pointer.
In fact we were working through all the wrong methods eg iterrows (slow) or
iterating over columns which created the need for a
transpose.
However, df.values.tolist() seems to create a list of row lists which is what
is actually needed and it is the fastest.
So to convert df to something for reportlab table this seems most efficient
rlab_table_data=[['Mean','Max','Min','TestA','TestB']]+df.values.tolist()
thanks again
--
Robin Becker
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