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a for loop which saves the result of a sampling dist in a dict
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| # from Udemy course: Data Science & Deep Learning for Business | |
| # stratum_white and stratum_red are Data Frames | |
| alcohol_per_wine_type = {} | |
| for stratum, wine_type in [(stratum_white, 'white'), (stratum_red, 'red')]: | |
| sample = stratum['alcohol'].sample(250, random_state = 0) # random sampling on each stratum | |
| alcohol_per_wine_type[wine_type] = sample.mean() | |
| print(alcohol_per_wine_type) |
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