Rounding entries in a Pandas DafaFrame

Question

Using :

newdf3.pivot_table(rows=['Quradate'],aggfunc=np.mean)

which yields:

           Alabama_exp  Credit_exp  Inventory_exp   National_exp    Price_exp   Sales_exp
Quradate                        
2010-01-15   0.568003    0.404481    0.488601    0.483097    0.431211    0.570755
2010-04-15   0.543620    0.385417    0.455078    0.468750    0.408203    0.564453

I'd like to get the decimal numbers rounded to two digit and multiplied by 100 eg .568003 should be 57 been fiddling with it for a while to no avail; tried this

newdf3.pivot_table(rows=['Quradate'],aggfunc=np.mean).apply(round(2)) #and got:
TypeError: ("'float' object is not callable", u'occurred at index Alabama_exp')

Tried a number of other approaches to no avail most complain about the item not being a float... I see that the Pandas series object has a round method but DF does not I tried using df.apply but it complained about the float issue.

Answer 1

Just use numpy.round, e.g.:

100 * np.round(newdf3.pivot_table(rows=['Quradate'], aggfunc=np.mean), 2) 

As long as round is appropriate for all column types, this works on a DataFrame.

With some data:

In [9]: dfrm
Out[9]:
          A         B         C
0 -1.312700  0.760710  1.044006
1 -0.792521 -0.076913  0.087334
2 -0.557738  0.982031  1.365357
3  1.013947  0.345896 -0.356652
4  1.278278 -0.195477  0.550492
5  0.116599 -0.670163 -1.290245
6 -1.808143 -0.818014  0.713614
7  0.233726  0.634349  0.561103
8  2.344671 -2.331232 -0.759296
9 -1.658047  1.756503 -0.996620

In [10]: 100*np.round(dfrm, 2)
Out[10]:
     A    B    C
0 -131   76  104
1  -79   -8    9
2  -56   98  137
3  101   35  -36
4  128  -20   55
5   12  -67 -129
6 -181  -82   71
7   23   63   56
8  234 -233  -76
9 -166  176 -100