Python Project Intro & Dirty Date Data 1 part1

Python Project Intro & Dirty Date Data 1 This is the first video in a series on my journey to try and do some data analysis on a greenhouse project where I’m trying to match plant information with the environmental conditions inside the greenhouse.I’d started a while back on doing Building Data Capture and processing from BIM models and recently subscribed to the free course on EDx which was the “Data Science for Construction, Architecture and Engineering” by National University of Singapore. Which used Python to do the data manipulation (https://courses.edx.org/courses/course-v1:NUS+DSBE001x+2T2021/fa0c90c2114b4ae79a071e28329ab87d/)A grower asked me to look at data from 3 different data sets and how they could be combined to give useful insights about the plants growing in the environment from the 3 datasets.The initial dataset was downloadable from a Dashboard via a CSV file and the date formats were all different. The initial issue is date data in string format with text and numbers and how to wrangle it into a usable Datetime format so that you can do date manipulations like subtracting one date from another and getting a useful answer. Link to zipfile here: https://drive.google.com/file/d/1O7qHUl4fk7_k1fP5HOWa4rK5vGHHQ5E_/view?usp=sharingSo this video is an overview of the journey and the issues I was confronted with and how I learned to use Python to help me solve those issues. I wanted to record my process. As I move forward and forget the early issues and my solutions so these videos will be a useful reference. I hope my experiences and code will be of use to you. Can you please give a thumbs up for the video. Muchas Gracias Please visit my blog for similar topics: https://cr8ive.tk
Kind regards, Max Drake