Our goal is to analyze sales data.
The first part of any data analysis or predictive modeling task is an initial exploration of the data. Even if you collected the data yourself and you already have a list of questions in mind that you want to answer, it is important to explore the data before doing any serious analysis, since oddities in the data can cause bugs and muddle your results. Before exploring deeper questions, you have to answer many simpler ones about the form and quality of data. That said, it is important to go into your initial data exploration with a big picture question in mind since the goal of your analysis should inform how you prepare the data.
The final dataset is formatted like this: 
Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data. It is done after data exploration and cleaning. When we do data analysis we answer questions corresponding to our dataset.The questions we need to answer is the following:
- What was the best month for sales? How much was earned that month?
- Which city had the highest number of sales?
- What time should we display advertisements to maximize likelihood of customer's buying product?
- What products are most often sold together?
- What product sold the most? Why do you think it sold the most?