jupyter-notebook

Jupyter Notebook SOP

When to Use

• User is writing or improving a Jupyter notebook
• User wants to share or publish a notebook as a report
• User has reproducibility issues (notebook works for them but not others)
• User wants to structure an analysis or ML experiment cleanly

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Part 1 — Recommended Notebook Structure

Use these sections in order. Each section is a Markdown cell followed by code cells.

1. Title & Metadata
2. Imports & Configuration
3. Data Loading
4. Exploratory Data Analysis (EDA)
5. Feature Engineering / Preprocessing
6. Modeling (if applicable)
7. Results & Conclusions
8. Appendix (optional)

Section 1 — Title & Metadata

# Analysis Title

**Author:** Your Name  
**Date:** 2025-05-18  
**Dataset:** dataset_name.csv (source / version)  
**Purpose:** One sentence on what question this notebook answers.  

## Summary
Key findings in 3-5 bullet points — fill in after completing the notebook.

Section 2 — Imports & Configuration

# ── Standard library ──────────────────────────────────────────────
import os
import json
from pathlib import Path
from datetime import datetime

# ── Data manipulation ──────────────────────────────────────────────
import numpy as np
import pandas as pd

# ── Visualization ─────────────────────────────────────────────────
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px

# ── ML (if needed) ────────────────────────────────────────────────
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler

# ── Config ────────────────────────────────────────────────────────
RANDOM_SEED = 42
DATA_DIR = Path("../data")
OUTPUT_DIR = Path("../outputs")
OUTPUT_DIR.mkdir(exist_ok=True)

# Display settings
pd.set_option("display.max_columns", 50)
pd.set_option("display.max_rows", 100)
pd.set_option("display.float_format", "{:.4f}".format)

plt.rcParams["figure.figsize"] = (12, 6)
plt.rcParams["figure.dpi"] = 100
sns.set_theme(style="whitegrid", palette="muted")

np.random.seed(RANDOM_SEED)
print(f"NumPy: {np.__version__}, Pandas: {pd.__version__}")