pythonnumpypandas
Ben Gorman

Ben Gorman

Life's a garden. Dig it.

You suspect your local grocery's been price gouging the ground beef. You and some friends decide to track the price of ground beef every day for 10 days. You've compiled the data into a Series called beef_prices, whose index represents the day of each recording.

import numpy as np
import pandas as pd
 
generator = np.random.default_rng(123)
beef_prices = pd.Series(
    data = np.round(generator.uniform(low=3, high=5, size=10), 2),
    index = generator.choice(10, size=10, replace=False)
)
 
print(beef_prices)
# 4    4.36
# 8    3.11
# 2    3.44
# 0    3.37
# 6    3.35
# 9    4.62
# 3    4.85
# 5    3.55
# 1    4.64
# 7    4.78
# dtype: float64

For example, beef was priced 3.37 on the first day, 4.64 on the second day, etc.

Determine which day had the biggest price increase from the prior day.


Solution

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