## Our Dataset

We used a public-domain dataset from Kaggle that contains information about international football matches between 1872 and 2018 . It contains information about 38759 matches (Fifa World Cup matches, Friendly matches, etc).

Our dataset looks like this:

## Data Preprocessing

We performed some prepropcessing operations on the data:

Data Cleaning

Some dates in the dataset were represented as yyyy-mm-dd, and some as yyyy/mm/dd. We changed all to yyyy/mm/dd format using Python and Pandas library.

Adding new columns to the dataset

a column that represents the winner team
a column to represent the difference in score
a column to show the continent of the home team
a column to show the continent of the away team

So the modified dataset looks like this:

We used Excel, Python, and Pandas library to do that.

Creating a new dataset

We created a new dataset that is derived from the original dataset. It looks like this:

## Insights From Data

We used Tableau to analyze the data and get insights from it.

Some of the insights are found on the following link
Interactive Tableau session

We also created a Python program that receives the names of two teams as an input, and produces a summary of all the matches between those two teams as an output.