PHPMem v2.0.1
Version
1.6.45
Uptime
17 days 12 hours 7 minutes 8 seconds
Memory
Total
512MB
Used
12,72MB (2.48%)
Free
499,28MB
Keys
Current
14 060
Total (since start)
40 994
Evictions
0
Reclaimed
760
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
15 / 1 024 max
Total
238 484
Rejected
0
llm:b5b5083d99b8ead85fa8d5dbe65cd12de99ebaa92306aa8f66c775fd495b8f06
Edit
The sample rows are in the result blocks above. They are 15 rows from the single table `raw.AI_Usage_and_Impact_on_Students_and_Professionals`, with one row per surveyed user. They mix students and professionals from countries including the Philippines, Canada, the US, Pakistan, Germany, India and Australia. They cover purposes such as Coding, Studying, Writing, Content Creation, Customer Support and Research. I haven't quoted individual `Monthly_Income` values because that column is person-identifying.
**What the sample shows about the data:**
- **Size and duplicates:** The table has 300 rows but only 288 distinct `User_ID`s, so some users appear more than once.
- **Missing values:** Gaps appear in several columns. `Productivity_Score` has 284 non-null values, `Accuracy_Rating` 285 and `Satisfaction_Score` 293. Blanks are also visible in `AI_Tool`, `AI_Purpose`, `Profession`, `Tasks_Performed`, `Country` and `Gender` in individual sample rows.
- **Inconsistent text in numeric columns:** Several columns that should be numeric are stored as text and contain unit strings. Examples are "16 yrs", "1.6 hrs", "6.5 hrs", and "$20" in `Monthly_AI_Cost`. They need cleaning before averaging.
- **Inconsistent categories:**
- `Gender` has 12 spellings, including Male, male, MALE, M, Female, F, Other and Non-binary, plus 10 blanks.
- `AI_Tool` has variants such as "Chat GPT", "chatgpt" and "copilot", and `Education_Level` has 17 variants, such as "undergrad" and "Undergraduate".
- Country casing varies, for example "france" and "india".
- **Mixed languages:** Some `Profession` and `Tasks_Performed` entries are in German, French or Portuguese.
- **Plausibility issues:** Some rows look implausible. A 16-year-old is listed with a Master's, and a 17-year-old with a PhD.
Across the non-null values, average productivity is about 5.23 (range 1.6–10), average satisfaction about 6.15 and average accuracy about 3.43.
The sample is a convenient set of 15 rows rather than a random draw. I can run a random sample or a stratified one, for example by user type or tool, if you want that.