write a python script to automate parse JSON files

1: I have a folder that has several hundred .json files (but this should not matter since files can be added or deleted) 2: Each .json files has several hundred JSON DATA OBJECTS with exact DATA STRUCTURE below... [{ "time": 1515513600, "close": 2.31, "high": 2.33, "low": 2.27, "open": 2.28, "volumefrom": 5390392.99, "volumeto": 12463380.06, "reference": "CORN" }, { .. ..},{ ...}] The above is array of JSON DATA object... values will change and will be different..BUT "keys" are same. The "time": VALUE from one JSON DATA OBJECT are 1 hr EXACT difference.. 3: What I need you to do is calculate -> mean, median, average, standard deviation, z-score for the "open" and "volumeto" datas ONLY.. FOR 1 YEAR EACH and 1 DAY EACH. 1st jan 2014 -> 31st december 2014 and so on... The new file generated by python script will have a JSON DATA OBJECT like this: [{ "timefrom": 1396944000, "timeto": 1396964000, "openmean": 472.23, "openmedian": 472.23, "openaverage": 472.23, "openstddeviation": 472.23, "openzscore": 472.23, "volumetomean": 472.23, "volumetomedian": 472.23, "volumetoaverage": 472.23, "volumetostddeviation": 472.23, "volumetozscore": 472.23, "reference": "CORN" }, { .... },{ ... }] HERE: "timefrom":..... is 1st Jan 2014.. and "timeto":..... is 31st december 2014.. those values are in UNIX TIME... remember that the python script has to do this automatically for all the files available on the folder that has files .json...also remember that alllll the files will have exact same JSON DATA OBJECT AND EACH JSON DATA OBJECT is 1 hour difference.. the "time".. 4: Things to note:... our data TIME starts from around 1st JAN 2014 ONLY... not before(like 2013)... and will go on.. it may go for 3 years like 2014 to 2017 or it may go from 2014 to 2015... the generated file should be called yearly{filename}.json AND day{filename}.json ... here {filename} is the name of original file parsed.. This is a fixed budget of 30$ with reoccurring projects and enhancement...