Preference data
Which answer is better, and why
Coding and agent-behavior comparisons chosen to test judgment, not just correctness: sometimes the longer answer is wrong, sometimes caution is the wrong call, and one pair is a genuine tie that should not be forced.
- 12 pairs
- 10 clear, 2 slight or tie
- Agent safety and honesty cases
- Raw and DPO formats
Summing a 20 GB CSV
pref-01
I need the total of the amount column in a 20 GB CSV. My laptop has 16 GB of RAM. How do I do it in Python?
Read it in chunks so only part of the file is in memory at once:
import pandas as pd
total = 0
for chunk in pd.read_csv("data.csv", usecols=["amount"], chunksize=1_000_000):
total += chunk["amount"].sum()
print(total)usecols skips the other columns, which cuts memory further. If amount has blanks, sum() skips NaN by default.
Load it with pandas and sum the column:
import pandas as pd
df = pd.read_csv("data.csv")
print(df["amount"].sum())If you run out of memory, try a machine with more RAM or close other programs.
Expert judgment
B loads the whole 20 GB file, which cannot fit in 16 GB of RAM (pandas usually needs several times the file size), and then tells the user to buy a bigger machine. A streams the file in chunks and reads only the needed column, so it works on the stated hardware. A also handles blanks correctly.