In Python, load the data with pandas and compute cost per thousand impressions from column totals for the whole period, or row by row for each month. On the sample data it returns 120.83.
CPM = Ad spend ÷ Impressions × 1,000
What you need
CPM (cost per mille) is what you pay for one thousand ad impressions: ad spend divided by impressions, times 1,000. You need these columns, here from the sample file monthly.csv:
- df["marketing_spend"]: marketing spend
- df["ad_impressions"]: ad impressions
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["cpm"] = df["marketing_spend"] / df["ad_impressions"] * 1000
print(df[["month", "cpm"]].round(2))
# Whole period: add up the parts first, then divide
cpm_total = df["marketing_spend"].sum() / df["ad_impressions"].sum() * 1000
print(round(cpm_total, 2))
What you should get
Run against the sample data, the code above returns these values:
| Month | marketing_spend | ad_impressions | cpm |
|---|---|---|---|
| 2026-01 | 96,000 | 8,20,000 | ₹117.07 |
| 2026-02 | 1,02,000 | 8,65,000 | ₹117.92 |
| 2026-03 | 1,18,000 | 9,40,000 | ₹125.53 |
| 2026-04 | 99,000 | 8,80,000 | ₹112.50 |
| 2026-05 | 1,24,000 | 9,90,000 | ₹125.25 |
| 2026-06 | 1,31,000 | 10,50,000 | ₹124.76 |
| Whole period | 6,70,000 | 55,45,000 | ₹120.83 |
₹6,70,000 ÷ 55,45,000 × 1,000 = ₹120.83
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 cost per thousand impressions misleads
- Impressions are not views. Platforms count an impression when an ad is served, even if nobody saw it.
- Compare CPM within a platform and placement; feeds, stories and search have very different prices.
- Spend that is not impression-based, such as influencer fees, should not be in the numerator.
The full explanation, with a calculator, is on the Cost per thousand impressions (CPM) 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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