In Python, load the data with pandas and compute shipping cost per order from column totals for the whole period, or row by row for each month. On the sample data it returns 70.00.
Shipping cost per order = Total shipping cost ÷ Number of orders
What you need
Shipping cost per order is what you pay couriers, on average, for each order: total shipping cost in a period divided by the number of orders shipped. You need these columns, here from the sample file monthly.csv:
- df["shipping_cost"]: shipping cost
- df["orders"]: orders
Step by step
- Install pandas (pip install pandas) and save monthly.csv next to your script.
- Run the script. The first print shows one row per month, the second the figure for the whole period.
- To use your own data, rename your columns to match, or change the names in the code.
The code
import pandas as pd
df = pd.read_csv("monthly.csv")
# Each month
df["shipping_per_order"] = df["shipping_cost"] / df["orders"]
print(df[["month", "shipping_per_order"]].round(2))
# Whole period: add up the parts first, then divide
shipping_per_order_total = df["shipping_cost"].sum() / df["orders"].sum()
print(round(shipping_per_order_total, 2))
What you should get
Run against the sample data, the code above returns these values:
| Month | shipping_cost | orders | shipping_per_order |
|---|---|---|---|
| 2026-01 | 49,100 | 702 | ₹69.94 |
| 2026-02 | 52,400 | 748 | ₹70.05 |
| 2026-03 | 56,800 | 812 | ₹69.95 |
| 2026-04 | 54,000 | 771 | ₹70.04 |
| 2026-05 | 59,200 | 846 | ₹69.98 |
| 2026-06 | 64,200 | 917 | ₹70.01 |
| Whole period | 3,35,700 | 4,796 | ₹70.00 |
₹3,35,700 ÷ 4,796 = ₹70.00
Notes for Python
- Dividing by zero in pandas does not raise an error: it gives inf or NaN. Check with df.replace([float("inf"), -float("inf")], float("nan")) before averaging or plotting.
- For the whole period, sum the columns first and then divide. df[col].mean() of the monthly results weights a small month the same as a large one.
- pct_change(), groupby() and resample() extend the same idea to weekly data, product categories and daily rows.
Where shipping cost per order misleads
- Include the cost of return and RTO shipments, or the figure looks lower than what you actually paid.
- Shipping charged to customers is revenue, not a reduction of cost. Keep the two apart.
- Courier invoices often arrive weeks late. Match costs to the month the order shipped, not the month the invoice came.
The full explanation, with a calculator, is on the Shipping cost per order page.
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About the data on this page
The figures come from a small made-up dataset, printed above in full so you can check every number by hand. Download it as monthly.csv. The results are computed from those rows when the page is built, and the Excel formulas, SQL and Python on these pages are run against the same rows before publishing, so the code and the answers agree.
To get these numbers from your own data without writing formulas, try AnalyzeIt: ask in plain words and it shows the working behind every figure.
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