Time series forecast

delivery pipeline

This readme explains the content of the directory and the execution steps to complete the delivery forcasts.

curves delivery curves

This project folder does not contain any script to retune or re perform a mapping or a prediction or run sanity checks, it just applies already pretrained models. In case of unconsistency please refer to the author.


In the project directory there is an example docker file for creating an ad hoc container.

proj_dir project directory

To install the basic libraries please run this script with python 3.6+. Depending on the required KPIs other graphic libraries might be installed.

All the scripts consider the variable $LAV_DIR which can be set as the current directory. Paths can be otherwise hard coded adjusted.

tdg/cronon production

jupyter jupyter notebook on Hungarian cluster

local production

mapping example of mapping result

regression results after regression


joyplot differences wrt previous delivery

Apply this script to sum up the results for the customer delivery and check the following KPIs:

sankey t-test feb-mar vs t-test mar-apr, change in ranking

internal meeting

boxplot differences in capture rate between deliveries

isocalendar check against isocalender

finalize the delivery

Run the script tank_delivery adjusting the output file name.

delivery finalize the delivery

customer support