I have taken a data analysis course with Kent Jones, so I decided to take this approach for analyzing and cleaning the data from the thermostats readings in the CSV file provided. I used VS code and python Jupiter notebook to complete my data analytics of the readings. I used python libraries pandas, numpy, matplotlib, seaborn, and scipy. What I did first was I cleaned the data removing new lines and empty spaces, it detects each run and counts it and creates a dictionary for each of the data entries and adds it to them which are T0, T1, ST, H and processes. Doing this allows me to be able to analyze all data for each new line since they are combined allows for separation to be able to analyze sats of each of them as well as creating graphs from this data. Added extra columns to be able to start more analyzing the data such as minute intervals, temperature differences, target temperature differences, control error, and the heating rate. I think the output is what I expected it seems like this is normal reading like everything seems to be working well and not much surprising or bad findings from the data analytics. It seems like the temp sensors about mid-way through were optimized because the data shows that basically there is less errors, less deviation, and the cycle load was less.
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