Decline Rate Calculator

Level 2

Chapter 4: NumPy & Pandas

descriptionProblem

Given a pandas DataFrame with a monthly oil rate, compute the month-over-month decline rate as a new column called "decline_pct":

\text{decline\_pct}_i = \frac{\text{rate}_{i-1} - \text{rate}_i}{\text{rate}_{i-1}} \times 100

Two requirements:

The first row has no previous month, so its decline_pct must be NaN.
Use df.shift() rather than a Python for loop. The whole column

should fall out of one vectorised expression.

Data:

month:  1     2    3    4    5    6
rate:   1000  920  860  800  760  720

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codeYour solution

main.py

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Try solving it yourself first — the hints walk you through it. The solution below is one valid approach; yours may differ and still be correct.

import pandas as pd

df = pd.DataFrame({
    "month": [1, 2, 3, 4, 5, 6],
    "rate":  [1000, 920, 860, 800, 760, 720],
})

prev = df["rate"].shift(1)
df["decline_pct"] = (prev - df["rate"]) / prev * 100

print(df)

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4.2 Production Data Loader

4.4 Data Cleaning Pipeline

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