Rounding calculated column to 1dp

Question

I am conscious this is a popular query but I haven't found anything on here that quite matches what I need. I have a column in a table that is rounding 36.25 to 36.2 rather than 36.3. Having read about this extensively on here I appreciate the details, however this doesn't help me solve my problem. How can I create some code that will round my 'Outcome' column as I wish please? This code produces a version of the df I am using:

import pandas as pd
import numpy as np

raw_data = {'AreaCode' : ['101', '102', '103', '104'],
            'Numerator' : [300, 500, 600, 667],
            'Denominator' : [1000, 780, 1100, 1840]}
Data = pd.DataFrame(raw_data, columns = ['AreaCode', 'Numerator', 'Denominator'])

And then i am trying to add an 'Outcome' column:

Data['Outcome'] = Data['Numerator'] / Data['Denominator'] * 100

Produces table below:

AreaCode|Numerator|Denominator|Outcome
101|300|1000|30.000000 
102|500|780|64.102564 
103|600|1100|54.545455
104|667|1840|36.25000

Which is fine except when I apply Data = Data.round(1) to this, it rounds 36.250000 to 36.2. I need this column to 1dp showing as 36.3 but how can I code this in Python. Examples on here of how to do this use strings of one-off, user-entered numbers, rather than an entire df.column. It won't let me pass my df.column into these. One example I tried which didn't work:

import math
def my_round(n, ndigits):
    part = n * 10 ** ndigits
    delta = part - int(part)
    # always round "away from 0"
    if delta >= 0.5 or -0.5 < delta <= 0:
        part = math.ceil(part)
    else:
        part = math.floor(part)
    return part / (10 ** ndigits

Answer 1

I made a little tweak to your function and it seems to work now :)

def my_round(n, ndigits=1):
    try:
       part = n * 10 ** ndigits
       delta = part - int(part)
       # always round "away from 0"
       if delta >= 0.5 or -0.5 < delta <= 0:
           part = math.ceil(part)
       else:
           part = math.floor(part)
       val =  part/(10 ** ndigits)
    except ValueError:
       val = np.nan
    return val

Data['Outcome'] = (Data['Numerator'].divide(Data['Denominator'])*100).apply(my_round)
print(Data)

Output:

  AreaCode  Numerator  Denominator  Outcome
0      101        300         1000     30.0
1      102        500          780     64.1
2      103        600         1100     54.5
3      104        667         1840     36.3

Answer 2

After importing pandas to your notebook, you can add this line so that your float values will not exceed one decimal place:

import pandas as pd
pd.options.display.float_format = '{:.1f}'.format