For this project, the lab supervisors would like to know how well the lab has delivered data to our partners. There are two main areas of interest. They are looking

for insights into data quality across projects on a monthly basis for 2023. For example, how many datapoints did the lab deliver, and what is the success rate (pass rate) each month of 2023. While data quality across all projects is important, leadership would also like to know how well each crop is performing in the lab as well. The lab's goal is to deliver data on 90% of all datapoints attempted each month. It would be great to understand if they are meeting that threshold. They would also like to know how well we are doing at delivering projects on time. Do we deliver on or before the due date? We usually define that as On Time Delivery (OTD). What is the average turnaround time (TAT)? Again, insights on a monthly basis would be great. Leadership is only concerned with the overall here, no need to look into how these metrics look like for each crop. Arrival date, expected due date, and project completion date are all provided. The lab is striving to hit an average OTD of 90% and TAT of 3 days. Using Python, read in the sample data (.csv) and provide insights into the two points above. Please provide a table(s) of the metrics. Plots would also be helpful. Many times, we have to present this data to leadership. A powerpoint slide or two or document sharing insights into this data would help organize everything, and make it easy to share. Please provide enough context so I can understand what each table/plot is showing. Please send me your solution code, slide/doc of insights (plots, tables, etc) DELIVERABLES :- 1) PPT (10-12 SLIDES) 2) Report (4-5 pages) 3) PYTHON - Solution code, slide/doc of insights (plots, tables, etc)