Lotto Top winners Numbers

Notebook by Pablo

import pandas as pd

df = pd.read_csv('C:/Users/pablo/Downloads/Loto.csv')

df.head()

	Draw Date	Winning Numbers	Multiplier
0	02/03/2010	17 22 36 37 52 24	2
1	02/06/2010	14 22 52 54 59 04	3
2	02/10/2010	05 08 29 37 38 34	5
3	02/13/2010	10 14 30 40 51 01	4
4	02/17/2010	07 08 19 26 36 15	3

df.tail()

	Draw Date	Winning Numbers	Multiplier
663	06/15/2016	04 22 24 31 33 10	2
664	06/18/2016	02 23 41 53 63 11	2
665	06/22/2016	14 40 42 43 52 17	3
666	06/25/2016	03 27 36 56 69 25	2
667	06/29/2016	23 29 37 60 64 06	2

df.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 668 entries, 0 to 667
Data columns (total 3 columns):
Draw Date          668 non-null object
Winning Numbers    668 non-null object
Multiplier         458 non-null float64
dtypes: float64(1), object(2)
memory usage: 20.9+ KB

df1 = df['Winning Numbers']

df1.head()

0    17 22 36 37 52 24
1    14 22 52 54 59 04
2    05 08 29 37 38 34
3    10 14 30 40 51 01
4    07 08 19 26 36 15
Name: Winning Numbers, dtype: object

s = df1.str.split(' ').apply(pd.Series, 1) 

s.head()

	0	1	2	3	4	5
0	17	22	36	37	52	24
1	14	22	52	54	59	04
2	05	08	29	37	38	34
3	10	14	30	40	51	01
4	07	08	19	26	36	15

len(s.index)

668

Function to get Top wining Numbers

def get_top_numbers(df):
    col = range(0,6)
    pick_list = []
    
    for column in col:
        pick_dict = {}
        if column == 0:
            ind = column + 1
        else:
            ind = 0
        top = df.groupby(column).count()
        top = top.sort_values(ind,ascending=False).head(2).reset_index()
        number = top[column][0]
        count = top[ind][0]
        
        pick_dict['Number'] = number
        pick_dict['count'] = count
        pick_dict['out of ']= len(df.index)
        
        pick_list.append(pick_dict)
        
    return pick_list

numbers = get_top_numbers(s)

Winning Numbers

Top Winning number from 2010 to 2016

numbers

[{'Number': '02', 'count': 51, 'out of ': 668},
 {'Number': '12', 'count': 35, 'out of ': 668},
 {'Number': '25', 'count': 27, 'out of ': 668},
 {'Number': '52', 'count': 32, 'out of ': 668},
 {'Number': '59', 'count': 54, 'out of ': 668},
 {'Number': '29', 'count': 27, 'out of ': 668}]

sanity check

g1 = s.groupby(2).count()

g1 = g1.sort_values(0,ascending=False).head(2).reset_index()

g1

	2	0	1	3	4	5
0	25	27	27	27	27	27
1	40	25	25	25	25	25

g1[1][0]

27