15. Chart Choice and Storytelling
15.1 Match Chart to Question
| Question | Chart |
|---|---|
| Compare GMV across cities | Bar (sorted) |
| Trend over days / hours | Line |
| Distribution of delivery mins | Hist or box |
| Share of statuses | Stacked bar or carefully used pie (max 3–4 slices) |
| City × status | Grouped bar / seaborn countplot hue |
# Sorted bars — easiest manager read
import matplotlib.pyplot as plt
import pandas as pd
gmv = pd.Series(
{"Pune": 220000, "Nashik": 140000, "Sambhaji Nagar": 80000,
"Nagpur": 90000, "Solapur": 70000, "Kolhapur": 65000}
).sort_values(ascending=True)
fig, ax = plt.subplots()
ax.barh(gmv.index, gmv.values)
ax.set_title("Where is fictional Oct GMV coming from?")
ax.set_xlabel("GMV (₹)")
plt.show()