ChatGPT can predit the correct code, but cannot predict output in analyzing CSV

I was using ChatGPT for analyzing a csv file...

The idea is to analyze CSV File, create a tables by making unique values in the table as headers..

Basically my query is this..

Section,Subject1,Subject2,Subject3,Subject4,Subject5,Subject6,Subject7 LKG A,3,2,2,3,4,3,3 LKG A,3,3,3,4,4,4,4 LKG A,3,3,4,4,4,4,3 LKG A,4,4,3,2,4,4,4 LKG A,3,4,4,4,4,4,3 LKG A,4,4,4,4,3,4,4 LKG A,4,4,4,4,4,4,4 LKG A,4,4,4,4,4,4,4 LKG A,4,4,4,4,4,4,4 LKG B,2,2,1,1,3,2,2 LKG B,1,2,2,2,4,2,2 LKG B,1,4,2,1,2,3,3 LKG B,2,2,2,3,4,3,2 LKG B,3,3,3,2,4,3,3 LKG B,3,3,3,3,3,3,3 LKG B,4,4,4,4,4,4,4 LKG B,4,4,4,4,4,4,4 LKG C,3,3,3,3,3,3,3 LKG C,3,4,4,4,4,4,4 LKG C,4,4,4,4,4,4,4 LKG D,3,4,3,4,3,4,3 etc...

The above data contains feedback given my each parent on a paricular subjects. Each row represents a feedback by one parent. First column is the section and other columns are feedback in subject..

Now., analyze and tell me the section and count of unique feedback receieved in each subject.

For each Subject 1 to 7

1. Put each row for each section and group all the count of unique feedback and print the below table for each subject.

2. Table header.

Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feed

Make each table for each section. 1. Put each row for each section (like "LKG A", "LKG B") and group all the count of unique feedback for that section and print the below table for each subject. 2. Table header. Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 | LKG A | 5 | 4 | 2 | 0

ChatGPT gave very correct python code which on running gave prefect output.

But when I asked chatGPT to predict output it gave flawed output every time.

Correct output: Subject: Subject1 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 5 | 4 | 0 | 0 LKG B | 2 | 2 | 2 | 2 LKG C | 1 | 2 | 0 | 0 LKG D | 0 | 1 | 0 | 0 UKG A | 4 | 2 | 0 | 1 UKG B | 4 | 5 | 0 | 0 UKG C | 1 | 2 | 1 | 0 UKG D | 5 | 2 | 0 | 0 Subject: Subject2 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 6 | 2 | 1 | 0 LKG B | 3 | 2 | 3 | 0 LKG C | 2 | 1 | 0 | 0 LKG D | 1 | 0 | 0 | 0 UKG A | 4 | 3 | 0 | 0 UKG B | 4 | 5 | 0 | 0 UKG C | 2 | 1 | 1 | 0 UKG D | 7 | 0 | 0 | 0 Subject: Subject3 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 6 | 2 | 1 | 0 LKG B | 2 | 2 | 3 | 1 LKG C | 2 | 1 | 0 | 0 LKG D | 0 | 1 | 0 | 0 UKG A | 5 | 2 | 0 | 0 UKG B | 4 | 4 | 1 | 0 UKG C | 1 | 2 | 1 | 0 UKG D | 5 | 2 | 0 | 0 etc...

ChatGPT Incorrect Output Here is the output of the modified code, with the data that you provided:

Subject: subject1 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 5 | 4 | 2 | 0 LKG B | 4 | 3 | 3 | 1 LKG C | 4 | 3 | 0 | 0 LKG D | 0 | 1 | 0 | 0 UKG A | 4 | 4 | 0 | 0 UKG B | 4 | 5 | 1 | 0 UKG C | 4 | 2 | 1 | 0 UKG D | 4 | 4 | 0 | 0

Subject: subject2 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 6 | 2 | 0 | 0 LKG B | 4 | 3 | 2 | 0 LKG C | 4 | 0 | 0 | 0 LKG D | 0 | 1 | 0 | 0 UKG A | 4 | 4 | 0 | 0 UKG B | 4 | 4 | 1 | 0 UKG C | 4 | 2 | 1 | 0 UKG D | 4 | 4 | 0 | 0

Subject: subject3 Section | Count of Feedback As 4 | Count of Feedback As 3 | Count of Feedback As 2 | Count of Feedback As 1 LKG A | 6 | 3 | 0 | 0 LKG B | 4 | 3 | 2 | 0 LKG C | 4 | 0 | 0 | 0 LKG D | 0 | 1 | 0 | 0 UKG A | 4 | 4 | 0 | 0 UKG B | 4 | 4 | 1 | 0 UKG C | 4 | 2 | 1 | 0

etc...