# how to calculate evolution change in percentage in a dataset compared to itself

scenario:

lets say I have a table for number of customers visiting a shop per day. now I want to calculate that how much change has happened in terms of number of visitors throughout the past 30 days and come up with a single value that tells me the change rate (in percentage). but I do not want to compare the changes of current month with the values of the previous month(s) instead I want to compare the current month with itself! I have some naive solutions but I am not a data scientist and am not sure if the solution would give me a meaningful value at all!

my first question: is this a meaningful question at all (to compare a data set with itself)?

my second question: if so, how would you approach the solution?

solution one: one solution that I thought about was to compare the value of the first day with the value of the last day, but then It seemed a bit stupid because values could fluctuate randomly in between and the result would not represent the fluctuations.

solution two: another solution that I could think of was to compare the value of each day (within the month) with the value of the day before it and then calculate the change ratio and finally accumulate all the ratios and come up with a single value!

side note: i would like to get both positive and negative percentage depending on the change ratio

2. Another idea is to set the value of first day as threshold and calculate the total negative (drop from threshold) and positive (raise from threshold) through the month. Let's say in a constant month (a month in which all 30 days have exact same values) the percentage of change is 0%. It means that sum of above-threshold values and under-threshold values can give you an estimate of change in percentage according to the first day. An example is [5, 10, 50, 100, 5, 1] visits during 6 days. we set the value of first day ($$5$$) as threshold. Then you will have [0%, 100%, 900%, 1900%, 0%, -400%] are the raises and falls (why?!) and you can use any numerical calculation to come up with a final number e.g. 2900% raise and 400% fall which can be 2500% raise at the end.