Bite 281. Generating sales reports from Github data

In this bite you will learn how to process the output from a Github API call and generate a summary sales report along with a yearly one. It’s up to you to decide how to approach this bite, with the exception of having to create a Pandas DataFrame from the data.

Summary Report

The summary report that you will generate will look like this by default:

                    sum          mean        max
        year
        2013  484247.51  40353.959167   81777.35
        2014  470532.51  39211.042500   75972.56
        2015  608473.83  50706.152500   97237.42
        2016  733947.03  61162.252500  118447.83

I’ve provided the global variable STATS, which is a list with sum, mean, max in it. This is what controls what is included in the summary report. That being said, the summary_report() function will include the optional stats variable, which should default to STATS.

Yearly Report

The yearly report should be as follows, for example:

        2013
                  sales
        month
        1      14236.90
        2       4519.89
        3      55691.01
        4      28295.35
        5      23648.29
        6      34595.13
        7      33946.39
        8      27909.47
        9      81777.35
        10     31453.39
        11     78628.72
        12     69545.62

The yearly_report() function, along with requiring the DataFrame to work from, takes a year variable which determines which year to report on. If the given year is not included in the report, a ValueError should be raised.

For example, lets say that the year 1800 was passed, the error message should be: "The year 1800 is not included in the report!"

Conclusion

Hopefully you will learn something new from this one. Go forth and dominate!