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
Robin Becker wrote:
> In conversion of pandas dataframe to reportlab table I suggested using
> this expression
>
> [list(x) for x in map(list,zip(*[df[i].values for i in df]))]
>
> which effectively transposes the dataframe. However, it's not clear that
> this works for a large number of rows.
In conversion of pandas dataframe to reportlab table I suggested using this
expression
[list(x) for x in map(list,zip(*[df[i].values for i in df]))]
which effectively transposes the dataframe. However, it's not clear that this works for a large number of rows. Is the argument *A
for A a large
