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chore(learn): Applied MDX format to Chinese curriculum files (#40462)

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Randell Dawson
2020-12-16 00:37:30 -07:00
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75
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/accessing-and-changing-elements,-rows,-columns.md
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@ -4,45 +4,50 @@ challengeType: 11
videoId: v-7Y7koJ_N0
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What code would change the values in the 3rd column of both of the following Numpy arrays to 20?
<section id='tests'>
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
````yml
question:
text: |
What code would change the values in the 3rd column of both of the following Numpy arrays to 20?
# Output:
# [[ 1 2 20 4 5]
# [ 6 7 20 9 10]]
```
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
## --answers--
# Output:
# [[ 1 2 20 4 5]
# [ 6 7 20 9 10]]
```
answers:
- |
```python
a[:, 3] = 20
```
- |
```python
a[2, :] = 20
```
- |
```python
a[:, 2] = 20
```
- |
```python
a[1, 2] = 20
```
solution: 3
````
```python
a[:, 3] = 20
```
---
```python
a[2, :] = 20
```
---
```python
a[:, 2] = 20
```
---
```python
a[1, 2] = 20
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

69
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/basics-of-numpy.md
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@ -4,42 +4,45 @@ challengeType: 11
videoId: f9QrZrKQMLI
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What will the following code print?
<section id='tests'>
```python
b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])
print(b)
```
````yml
question:
text: |
What will the following code print?
## --answers--
```python
b = np.array([[1.0,2.0,3.0],[3.0,4.0,5.0]])
print(b)
```
answers:
- |
```python
[[1.0 2.0 3.0]
[3.0 4.0 5.0]]
```
- |
```python
[[1. 2. 3.]
[3. 4. 5.]]
```
- |
```python
[[1. 3.]
[2. 4.]
[3. 5.]
```
solution: 2
````
```python
[[1.0 2.0 3.0]
[3.0 4.0 5.0]]
```
---
```python
[[1. 2. 3.]
[3. 4. 5.]]
```
---
```python
[[1. 3.]
[2. 4.]
[3. 5.]
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

64
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/copying-arrays-warning.md
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@ -4,42 +4,44 @@ challengeType: 11
videoId: iIoQ0_L0GvA
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What is the value of `a` after running the following code?
<section id='tests'>
```py
import numpy as np
````yml
question:
text: |
What is the value of `a` after running the following code?
a = np.array([1, 2, 3, 4, 5])
b = a
b[2] = 20
```
```py
import numpy as np
## --answers--
a = np.array([1, 2, 3, 4, 5])
b = a
b[2] = 20
```
```python
[1 2 3 4 5]
```
answers:
- |
```python
[1 2 3 4 5]
```
- |
```python
[1 2 20 4 5]
```
- |
```python
[1 20 3 4 5]
```
solution: 2
````
---
```python
[1 2 20 4 5]
```
---
```python
[1 20 3 4 5]
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

84
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/initialize-array-problem.md
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@ -4,57 +4,59 @@ challengeType: 11
videoId: 0jGfH8BPfOk
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What is another way to produce the following array?
<section id='tests'>
```py
[[1. 1. 1. 1. 1.]
[1. 0. 0. 0. 1.]
[1. 0. 9. 0. 1.]
[1. 0. 0. 0. 1.]
[1. 1. 1. 1. 1.]]
```
````yml
question:
text: |
What is another way to produce the following array?
## --answers--
```py
[[1. 1. 1. 1. 1.]
[1. 0. 0. 0. 1.]
[1. 0. 9. 0. 1.]
[1. 0. 0. 0. 1.]
[1. 1. 1. 1. 1.]]
```
```py
output = np.ones((5, 5))
answers:
- |
```py
output = np.ones((5, 5))
z = np.zeros((3, 3))
z[1, 1] = 9
z = np.zeros((3, 3))
z[1, 1] = 9
output[1:-1, 1:-1] = z
```
output[1:-1, 1:-1] = z
```
- |
```py
output = np.ones((5, 5))
---
z = np.zeros((3, 3))
z[1, 1] = 9
```py
output = np.ones((5, 5))
output[1:3, 1:3] = z
```
- |
```py
output = np.ones((5, 5))
z = np.zeros((3, 3))
z[1, 1] = 9
z = np.zeros((3, 3))
z[1, 1] = 9
output[1:3, 1:3] = z
```
output[4:1, 4:1] = z
```
solution: 1
````
---
```py
output = np.ones((5, 5))
z = np.zeros((3, 3))
z[1, 1] = 9
output[4:1, 4:1] = z
```
## --video-solution--
1
# --hints--
# --solutions--
</section>

65
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/initializing-different-arrays.md
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@ -4,41 +4,44 @@ challengeType: 11
videoId: CEykdsKT4U4
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What will the following code print?
<section id='tests'>
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
````yml
question:
text: |
What will the following code print?
print(np.full_like(a, 100))
```
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
## --answers--
print(np.full_like(a, 100))
```
answers:
- |
```py
[[100 100 100 100 100]]
```
- |
```py
[[100 100 100 100 100]
[100 100 100 100 100]]
```
- |
```py
[[ 1 2 3 4 5]
[ 6 7 20 9 10]]
```
solution: 2
````
```py
[[100 100 100 100 100]]
```
---
```py
[[100 100 100 100 100]
[100 100 100 100 100]]
```
---
```py
[[ 1 2 3 4 5]
[ 6 7 20 9 10]]
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

80
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/loading-data-and-advanced-indexing.md
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@ -4,54 +4,56 @@ challengeType: 11
videoId: tUdBZ7pF8Jg
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
Given a file named `data.txt` with these contents:
<section id='tests'>
```
29,97,32,100,45
15,88,5,75,22
```
````yml
question:
text: |
Given a file named `data.txt` with these contents:
What code would produce the following array?
```
29,97,32,100,45
15,88,5,75,22
```
```py
[29. 32. 45. 15. 5. 22.]
```
What code would produce the following array?
## --answers--
```py
[29. 32. 45. 15. 5. 22.]
```
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.any(filedata < 50)
answers:
- |
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.any(filedata < 50)
print(output)
```
print(output)
```
- |
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.all(filedata < 50, axis=1)
---
print(output)
```
- |
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = filedata[filedata < 50]
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = np.all(filedata < 50, axis=1)
print(output)
```
solution: 3
````
print(output)
```
---
```py
filedata = np.genfromtxt('data.txt', delimiter=',')
output = filedata[filedata < 50]
print(output)
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

72
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/mathematics.md
View File

@ -4,45 +4,49 @@ challengeType: 11
videoId: 7txegvyhtVk
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What is the value of `b` after running the following code?
<section id='tests'>
```py
import numpy as np
````yml
question:
text: |
What is the value of `b` after running the following code?
a = np.array(([1, 2, 3, 4, 5], [6, 7, 8, 9, 10]))
b = np.max(a, axis=1).sum()
```
```py
import numpy as np
## --answers--
a = np.array(([1, 2, 3, 4, 5], [6, 7, 8, 9, 10]))
b = np.max(a, axis=1).sum()
```
```py
10
```
answers:
- |
```py
10
```
- |
```py
7
```
- |
```py
5
```
- |
```py
15
```
solution: 4
````
---
```py
7
```
---
```py
5
```
---
```py
15
```
## --video-solution--
4
# --hints--
# --solutions--
</section>

77
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/reorganizing-arrays.md
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@ -4,46 +4,49 @@ challengeType: 11
videoId: VNWAQbEM-C8
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
What code would produce the following array?
<section id='tests'>
```py
[[1. 1.]
[1. 1.]
[1. 1.]
[1. 1.]]
```
````yml
question:
text: |
What code would produce the following array?
## --answers--
```py
[[1. 1.]
[1. 1.]
[1. 1.]
[1. 1.]]
```
answers:
- |
```py
a = np.ones((2, 4))
b = a.reshape((4, 2))
print(b)
```
- |
```py
a = np.ones((2, 4))
b = a.reshape((2, 4))
print(b)
```
- |
```py
a = np.ones((2, 4))
b = a.reshape((8, 1))
print(b)
```
solution: 1
````
```py
a = np.ones((2, 4))
b = a.reshape((4, 2))
print(b)
```
---
```py
a = np.ones((2, 4))
b = a.reshape((2, 4))
print(b)
```
---
```py
a = np.ones((2, 4))
b = a.reshape((8, 1))
print(b)
```
## --video-solution--
1
# --hints--
# --solutions--
</section>

46
curriculum/challenges/chinese/08-data-analysis-with-python/numpy/what-is-numpy.md
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@ -4,30 +4,34 @@ challengeType: 11
videoId: 5Nwfs5Ej85Q
---
## Description
# --question--
<section id='description'>
</section>
## --text--
## Tests
Why are Numpy arrays faster than regular Python lists?
<section id='tests'>
## --answers--
```yml
question:
text: |
Why are Numpy arrays faster than regular Python lists?
Numpy does not perform type checking while iterating through objects.
answers:
- |
Numpy does not perform type checking while iterating through objects.
- |
Numpy uses fixed types.
- |
Numpy uses contiguous memory.
- |
All of the above.
solution: 4
```
---
Numpy uses fixed types.
---
Numpy uses contiguous memory.
---
All of the above.
## --video-solution--
4
# --hints--
# --solutions--
</section>