osairps / blog_mega_sena

Statistical analysis of Brazilian largest lottery.

Mega Sena Statistics:

Overview

Creating statistics on 'Mega-Sena' lottery results.

Methods

• Data cleaning , EDA and Statistic was made using Pandas and Numpy librarys in Python.
• Plots using matplotlib.pyplot library.
• Words were tokenized using CountVectorize from sklearn library

Results

• Numbers 10, 5, 53, 4, 23 where the most frequent.
• Numbers 9, 22, 55, 21, 26 where the less frequent.
• Even and Odd numbers almost had the same frequency (50.4 and 49.6 respectively).
• Numbers from 1-10 are present in 17.02% of draws (highest).
• Numbers from 21-30 are present in 16.34% of draws(lowest).
• Number combination 29,38,50 was present in 8 draws.(highest)

Softwares Used

• Jupyter notebook
• Python 3.6
• Powerpoint

Notebooks:

1. mega_sena.ipynb

Datasets

Mega-Sena results

Data Dictionary

Label	Type	Description
draw	int64	Number of the draw
data	object	Date of the draw (dd/MM/YYYY)
num1	int64	1st winning number in the draw
num2	int64	2st winning number in the draw
num3	int64	3st winning number in the draw
num4	int64	4st winning number in the draw
num5	int64	5st winning number in the draw
num6	int64	6st winning number in the draw
is_even	int64	Dummy: 1 for even, 0 for odd