تحلیل داده های سری زمانی
دو سال پیش منتشر شده
تعداد بازدید: 439
کد پروژه: 304977
شرح پروژه
For the tasks 3,4,5,6,7 compute and save in a csv file "timing.csv" the execution time required for the code to run
- Import datas into pandas from the .csv file
- Explore them with the features you consider relevant and perform, evenually, data cleaning to remove data inconsistency
- Print and save a stacked line graph ("Graph1") representing the weekly consumption in MW/h and comparing the years from 2006 to 2016
- For each year identify the day with the highest consumptions and the day with the lowest consumptions. Plot a graph that represents the evolution of the consumption during these days, in order to obtain a comparison between "peak-days" over the years.
- Identify the 10 days where the delta between the energy consumed in that day and in the day after is greater (that means higher adaptation stress on the production plants).
- Create and export as a CSV a dataset called "ProductionSchedule". Set it up with a daily basis and for each day provide:
- The total energetic production needed to cover the full consumption of the next day.
- The average power consumption during the next day
- The standard deviation of the consumption during the next day
- OPTIONAL: On an hour basis mark the time periods where the consumption is higher than: average + 3*standard deviation of the prediciton for that days. And plot the data for one month of your choice.
مهارت ها و تخصص های مورد نیاز
بودجه
100,000 تومان تا 300,000 تومان
مهلت برای انجام
3روز
وضعیت مناقصه
انجام شده
درباره کارفرما
عضویت سه سال پیش
