Sharon Machlis
I asked for visualizations, and it responded:
There are many interesting variables we could visualize. Let me suggest a few possibilities:
Suggested next steps:
Can you create a histogram of game total scores to see the distribution of scoring?
Could you make a box plot comparing home vs away team scores?
Let's create a scatter plot of temperature vs total score to see if weather affects scoring.
Can you show me the distribution of betting spreads and how they relate to actual game results?
Could you create a visualization showing win/loss records by team?
Which of these interests you, or would you like to explore something else in the data? I can help create any type of visualization you'd find useful!I asked for the weather versus scoring plot, and it wrote R code that unfortunately didn’t show an interesting trend. Next, I tried the histogram of total scoring, which returned R code, the bot’s observations, and a plot. Databot then provided the following analysis:
This visualization reveals several interesting patterns about NFL scoring:
1. The distribution looks approximately normal (bell-shaped), with some slight right skew
2. The mean total score is about 44.5 points
3. The median is very close to the mean at about 44 points
4. Most games fall between roughly 30 and 60 total points
5. There are a few outlier games with very high scoring (80+ points) and very low scoring (<20 points)
Sharon Machlis
While many mainstream chatbots have similar capabilities, few write and run R code like this; generative AI data analysis code is typically done in Python.
