SO I DID IT! AUTOMATED DATA PREPARATION AND MATCHING SOLUTION WITH PANDAS DATA FRAMES. ADS VIDEO WILL RELEASED SOON.
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So my solutions was to process text files to necessary formats and data structure easily to import to Pandas as text frame. Thus I did worthy from business point of view worthy service programming solution to prepare and easily import data to Pandas library. Self-made Canopy Data Import Tool/This is the first blog in a series. See the second blog here: Handling Missing Values iPandas DataFrames: the Hard Way, and the Easy Way Data exploration, manipulation, and visualization start with loading data, be it from files or from a URL. Pandas has become the go-to library for all things data analysis in Python, but if your intention is to jump straight into data exploration and manipulation, the Canopy Data Import Tool can help, instead of having to learn the details of
Today I found that I do not have possibility to integrate all scripts in one running consecutively since I use many operations of glob library which require script to be in environment folder, and I cannot run with os.system command script wihich is in executed by os.system command. So no possibility to integrate os.system("") run os.system("") I need to look for other possibilities. os.system is command of python os library Miscellaneous operating system interfaces. So I need to research possibilities of suprocesses and test them. All the rest is debugged and just pandas program rows shall be added. You can automate python scripts also with Windows Task Schedule, various automation python projects, subprocess library, threading library . Multithread automations scripts programming tutorials can be found on Youtube.
Planning and visualization is not a waste of time, but classification of processes which help to reduce error and time for implementation. Temptation to do start and to do fast and to classify or describe sufficiently cost much time. You avoid errors of multiple tasks and multiple relations mistakes.
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