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18 lines
763 B
18 lines
763 B
2 years ago
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# Exercise 7: NaN
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The goal of this exercise is to learn to deal with missing data in NumPy and to manipulate NumPy arrays.
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Let us consider a 2-dimensional array that contains the grades at the past two exams. Some of the students missed the first exam. As the grade is missing it has been replaced with a `NaN`.
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1. Using `np.where` create a third column that is equal to the grade of the first exam if it exists and the second else. Add the column as the third column of the array.
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**Using a for loop or if/else statement is not allowed in this exercise.**
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```python
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import numpy as np
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generator = np.random.default_rng(123)
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grades = np.round(generator.uniform(low = 0.0, high = 10.0, size = (10, 2)))
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grades[[1,2,5,7], [0,0,0,0]] = np.nan
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print(grades)
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```
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