ChatGPT (with a plus account) have launched an application in BETA to try - Code Interpreter that can be used to produce the start of of an analysis of data. Producing Python code for the analysis - Pandas based.
Prompt 1
So load in a file of COVID data from 2021 and type in the prompt "Acts as a data scientist and analze the datashet amd make charts and graphs to show major trends" Even with the spelling mistakes it did the following:
Acts as a data scientist and analze the datashet amd make charts and
graphs to show major trends
covid_1.csv
ChatGPT
Great, let's start by loading the dataset and examining its structure.
Finished working
Show work
It seems like the dataset does not have any column names. The dataset
consists of three columns. Could you please provide some context about what
these columns represent? This will help me to analyze the data more accurately.
first column is days, the second is group under 35 years old and third colum is a group over 35 years old
ChatGPT
Thank you for the clarification. Let's assign appropriate column names and take a look at some basic statistics of the data.
Finished working
RESULT
Day Group_Under_35 Group_Over_35
count 158.000000 158.000000 158.000000
mean 80.500000 0.009439 0.012779
std 45.754781 0.005514 0.007603
min 2.000000 0.000696 0.000414
25% 41.250000 0.005688 0.007028
50% 80.500000 0.008524 0.012666
75% 119.750000 0.013676 0.018399
max 159.000000 0.019054 0.026756
The dataset contains 158 records, spanning from day 2 to day 159.
Here are some basic statistics for each column:
- Group_Under_35: The average is around 0.0094, with a minimum value of 0.0007 and a maximum value of 0.0190. The data varies around this average by about 0.0055 (standard deviation).
- Group_Over_35: The average is around 0.0128, with a minimum value of 0.0004 and a maximum value of 0.0268. The data varies around this average by about 0.0076 (standard deviation).
Now, let's create some plots to visualize these trends. We'll make line plots for each group over the given days. This can give us a sense of how the values change over time for each age group.
Finished working
The line graph provides a visual representation of the trend in the dataset for both groups. From the graph, we can observe that:
- For both groups, the trend is generally increasing over time, suggesting that the value for both groups under 35 and over 35 grows as days pass.
- The 'Group Over 35' consistently has higher values than the 'Group Under 35'. This could suggest that the factor being measured impacts the 'Group Over 35' more significantly, or it could mean that there are more people in the 'Group Over 35'.
Remember, the precise interpretation would depend on what these values represent. For a more in-depth analysis, one could also look into statistical tests, correlation analysis, and more.
Do you have any specific questions or areas you'd like to explore in this data?
