wehub-resource-sync
72 lines
1.7 KiB
Markdown
72 lines
1.7 KiB
Markdown
# CSV Sum
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**Task:** "Write Python code that reads sales.csv and sums the 'amount' column."
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Verbatim model output from a benchmark run, Claude Haiku 4.5, no-skill arm vs ponytail arm, temperature 1, source `benchmarks/output.json`. Reproduce: `npx promptfoo@latest eval -c benchmarks/promptfooconfig.yaml`.
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## Without Ponytail, 20 lines of code
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# Python code to read sales.csv and sum the 'amount' column
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```python
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import pandas as pd
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# Read the CSV file
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df = pd.read_csv('sales.csv')
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# Sum the 'amount' column
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total_amount = df['amount'].sum()
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# Print the result
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print(f"Total amount: ${total_amount:,.2f}")
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```
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## Alternative methods:
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**Using CSV module (without pandas):**
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```python
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import csv
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total_amount = 0
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with open('sales.csv', 'r') as file:
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reader = csv.DictReader(file)
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for row in reader:
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total_amount += float(row['amount'])
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print(f"Total amount: ${total_amount:,.2f}")
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```
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**Using pandas with error handling:**
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```python
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import pandas as pd
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try:
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df = pd.read_csv('sales.csv')
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total_amount = df['amount'].sum()
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print(f"Total amount: ${total_amount:,.2f}")
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except FileNotFoundError:
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print("Error: sales.csv not found")
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except KeyError:
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print("Error: 'amount' column not found")
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```
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**The pandas method is recommended** because it's:
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- More concise and readable
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- Handles data types automatically
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- Provides built-in error handling
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- Efficient for large files
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## With Ponytail, 3 lines of code
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```python
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import csv
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total = sum(float(row['amount']) for row in csv.DictReader(open('sales.csv')))
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print(total)
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```
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Skipped: pandas, error handling, file closing, add when the CSV is large, malformed, or you need more analysis.
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**20 → 3 lines of code**, same model, same prompt.
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