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

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52
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-a.md
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@ -4,32 +4,40 @@ challengeType: 11
videoId: nVAaxZ34khk
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8)
<section id='tests'>
# --question--
```yml
question:
text: |
What does the shape of our dataframe tell us?
## --text--
answers:
- |
The size in gigabytes the dataframe we loaded into memory is.
- |
How many rows and columns our dataframe has.
- |
How many rows the source data had before loading.
- |
How many columns the source data had before loading.
solution: 2
```
What does the shape of our dataframe tell us?
## --answers--
The size in gigabytes the dataframe we loaded into memory is.
---
How many rows and columns our dataframe has.
---
How many rows the source data had before loading.
---
How many columns the source data had before loading.
## --video-solution--
2
# --hints--
# --solutions--
</section>

46
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-b.md
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@ -4,30 +4,36 @@ challengeType: 11
videoId: 0kJz0q0pvgQ
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-pandas-real-life-example-24fa5bf8)
<section id='tests'>
# --question--
```yml
question:
text: |
What does the <code>loc</code> method allow you to do?
## --text--
answers:
- |
Retrieve a subset of rows and columns by supplying interger-location arguments.
- |
Access a group of rows and columns by supplying label(s) arguments.
- |
Returns the first <code>n</code> rows based on the integer argument supplied.
solution: 2
```
What does the `loc` method allow you to do?
## --answers--
Retrieve a subset of rows and columns by supplying interger-location arguments.
---
Access a group of rows and columns by supplying label(s) arguments.
---
Returns the first `n` rows based on the integer argument supplied.
## --video-solution--
2
# --hints--
# --solutions--
</section>

53
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-and-visualizations.md
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@ -4,33 +4,40 @@ challengeType: 11
videoId: mHjxzFS5_Z0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59)
<section id='tests'>
# --question--
````yml
question:
text: |
When using Matplotlib's global API, what does the order of numbers mean here?
```py
plt.subplot(1, 2, 1)
```
## --text--
answers:
- |
My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.
- |
I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.
- |
My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.
solution: 3
````
When using Matplotlib's global API, what does the order of numbers mean here?
```py
plt.subplot(1, 2, 1)
```
## --answers--
My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.
---
I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.
---
My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.
## --video-solution--
3
# --hints--
# --solutions--
</section>

46
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-duplicates.md
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@ -4,30 +4,36 @@ challengeType: 11
videoId: kj7QqjXhH6A
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59)
<section id='tests'>
# --question--
```yml
question:
text: |
The Python method `.duplicated()` returns a boolean Series for your DataFrame. `True` is the return value for rows that:
## --text--
answers:
- |
contain a duplicate, where the value for the row contains the first occurrence of that value.
- |
contain a duplicate, where the value for the row is at least the second occurrence of that value.
- |
contain a duplicate, where the value for the row contains either the first or second occurrence.
solution: 2
```
The Python method `.duplicated()` returns a boolean Series for your DataFrame. `True` is the return value for rows that:
## --answers--
contain a duplicate, where the value for the row contains the first occurrence of that value.
---
contain a duplicate, where the value for the row is at least the second occurrence of that value.
---
contain a duplicate, where the value for the row contains either the first or second occurrence.
## --video-solution--
2
# --hints--
# --solutions--
</section>

86
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-introduction.md
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@ -4,53 +4,59 @@ challengeType: 11
videoId: ovYNhnltVxY
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
import numpy as np
What will the following code print out?
s = pd.Series(['a', 3, np.nan, 1, np.nan])
```py
import pandas as pd
import numpy as np
print(s.notnull().sum())
```
s = pd.Series(['a', 3, np.nan, 1, np.nan])
answers:
- |
3
- |
```
0 True
1 True
2 False
3 True
4 False
dtype: bool
```
- |
```
0 False
1 False
2 True
3 False
4 True
dtype: bool
```
solution: 1
````
print(s.notnull().sum())
```
## --answers--
3
---
```
0 True
1 True
2 False
3 True
4 False
dtype: bool
```
---
```
0 False
1 False
2 True
3 False
4 True
dtype: bool
```
## --video-solution--
1
# --hints--
# --solutions--
</section>

102
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-with-dataframes.md
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@ -4,61 +4,67 @@ challengeType: 11
videoId: sTMN_pdI6S0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/data-cleaning-rmotr-freecodecamp-fd76fa59)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
import numpy as np
What will the following code print out?
s = pd.Series([np.nan, 1, 2, np.nan, 3])
s = s.fillna(method='ffill')
```py
import pandas as pd
import numpy as np
print(s)
```
s = pd.Series([np.nan, 1, 2, np.nan, 3])
s = s.fillna(method='ffill')
answers:
- |
```
0 1.0
1 1.0
2 2.0
3 3.0
4 3.0
dtype: float64
```
- |
```
0 NaN
1 1.0
2 2.0
3 2.0
4 3.0
dtype: float64
```
- |
```
0 NaN
1 1.0
2 2.0
3 NaN
4 3.0
dtype: float64
```
solution: 2
````
print(s)
```
## --answers--
```
0 1.0
1 1.0
2 2.0
3 3.0
4 3.0
dtype: float64
```
---
```
0 NaN
1 1.0
2 2.0
3 2.0
4 3.0
dtype: float64
```
---
```
0 NaN
1 1.0
2 2.0
3 NaN
4 3.0
dtype: float64
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

49
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/how-to-use-jupyter-notebooks-intro.md
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@ -4,31 +4,38 @@ challengeType: 11
videoId: h8caJq2Bb9w
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
- <a href="https://twitter.com/rmotr_com/status/1122176794696847361" target='_blank'>Twitter Cheat Sheet</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f)
<section id='tests'>
\- [Twitter Cheat Sheet](https://twitter.com/rmotr_com/status/1122176794696847361)
```yml
question:
text: |
What is **not** allowed in a Jupyter Notebook's cell?
# --question--
answers:
- |
Markdown
- |
Python code
- |
An Excel sheet
solution: 3
```
## --text--
What is **not** allowed in a Jupyter Notebook's cell?
## --answers--
Markdown
---
Python code
---
An Excel sheet
## --video-solution--
3
# --hints--
# --solutions--
</section>

52
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/introduction-to-data-analysis.md
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@ -4,32 +4,40 @@ challengeType: 11
videoId: VJrP2FUzKP0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://docs.google.com/presentation/d/1fDpjlyMiOMJyuc7_jMekcYLPP2XlSl1eWw9F7yE7byk" target='_blank'>Slides</a>
</section>
## Tests
\- [Slides](https://docs.google.com/presentation/d/1fDpjlyMiOMJyuc7_jMekcYLPP2XlSl1eWw9F7yE7byk)
<section id='tests'>
# --question--
```yml
question:
text: |
Why should you choose R over Python for data analysis?
## --text--
answers:
- |
It's simple to learn.
- |
It's better at dealing with advanced statistical methods.
- |
There are many powerful libraries that support R.
- |
It's free and open source.
solution: 2
```
Why should you choose R over Python for data analysis?
## --answers--
It's simple to learn.
---
It's better at dealing with advanced statistical methods.
---
There are many powerful libraries that support R.
---
It's free and open source.
## --video-solution--
2
# --hints--
# --solutions--
</section>

49
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-cells.md
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@ -4,31 +4,38 @@ challengeType: 11
videoId: 5PPegAs9aLA
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
- <a href="https://twitter.com/rmotr_com/status/1122176794696847361" target='_blank'>Twitter Cheat Sheet</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f)
<section id='tests'>
\- [Twitter Cheat Sheet](https://twitter.com/rmotr_com/status/1122176794696847361)
```yml
question:
text: |
Which cells are responsible for rich display?
# --question--
answers:
- |
Code Cells
- |
Markdown Cells
- |
Raw Cells
solution: 1
```
## --text--
Which cells are responsible for rich display?
## --answers--
Code Cells
---
Markdown Cells
---
Raw Cells
## --video-solution--
1
# --hints--
# --solutions--
</section>

61
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-importing-and-exporting-data.md
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@ -4,35 +4,46 @@ challengeType: 11
videoId: k1msxD3JIxE
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f" target='_blank'>Notebook</a>
- <a href="https://twitter.com/rmotr_com/status/1122176794696847361" target='_blank'>Twitter Cheat Sheet</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/interactive-jupyterlab-tutorial-ac5fa63f)
<section id='tests'>
\- [Twitter Cheat Sheet](https://twitter.com/rmotr_com/status/1122176794696847361)
```yml
question:
text: |
What kind of data can you import and work with in a Jupyter Notebook?
# --question--
answers:
- |
Excel files.
- |
CSV files.
- |
XML files.
- |
Data from an API.
- |
All of the above.
solution: 5
```
## --text--
What kind of data can you import and work with in a Jupyter Notebook?
## --answers--
Excel files.
---
CSV files.
---
XML files.
---
Data from an API.
---
All of the above.
## --video-solution--
5
# --hints--
# --solutions--
</section>

52
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-algebra-and-size.md
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@ -4,32 +4,40 @@ challengeType: 11
videoId: XAT97YLOKD8
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
```yml
question:
text: |
What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?
## --text--
answers:
- |
Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
- |
NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
- |
NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
- |
Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
solution: 4
```
What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?
## --answers--
Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
---
NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
---
NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
---
Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
## --video-solution--
4
# --hints--
# --solutions--
</section>

82
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-arrays.md
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@ -4,50 +4,56 @@ challengeType: 11
videoId: VDYVFHBL1AM
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
A = np.array([
['a', 'b', 'c'],
['d', 'e', 'f'],
['g', 'h', 'i']
])
What will the following code print out?
print(A[:, :2])
```
```py
A = np.array([
['a', 'b', 'c'],
['d', 'e', 'f'],
['g', 'h', 'i']
])
answers:
- |
```python
[['a' 'b']]
```
- |
```py
[['b' 'c']
['e' 'f']
['h' 'i']]
```
- |
```py
[['a' 'b']
['d' 'e']
['g' 'h']]
```
solution: 3
````
print(A[:, :2])
```
## --answers--
```python
[['a' 'b']]
```
---
```py
[['b' 'c']
['e' 'f']
['h' 'i']]
```
---
```py
[['a' 'b']
['d' 'e']
['g' 'h']]
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

77
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-boolean-arrays.md
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@ -4,45 +4,54 @@ challengeType: 11
videoId: N1ttsMmcVMM
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
a = np.arange(5)
What will the following code print out?
print(a <= 3)
```
answers:
- |
```python
[False, False, False, False, True]
```
- |
```python
[5]
```
- |
```python
[0, 1, 2, 3]
```
- |
```python
[True, True, True, True, False]
```
solution: 4
````
```py
a = np.arange(5)
print(a <= 3)
```
## --answers--
```python
[False, False, False, False, True]
```
---
```python
[5]
```
---
```python
[0, 1, 2, 3]
```
---
```python
[True, True, True, True, False]
```
## --video-solution--
4
# --hints--
# --solutions--
</section>

46
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-a.md
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@ -4,30 +4,36 @@ challengeType: 11
videoId: P-JjV6GBCmk
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
```yml
question:
text: |
Why is Numpy an important, but unpopular Python library?
## --text--
answers:
- |
Often you won't work directly with Numpy.
- |
It's is extremely slow.
- |
Working with Numpy is difficult.
solution: 1
```
Why is Numpy an important, but unpopular Python library?
## --answers--
Often you won't work directly with Numpy.
---
It's is extremely slow.
---
Working with Numpy is difficult.
## --video-solution--
1
# --hints--
# --solutions--
</section>

53
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-b.md
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@ -4,31 +4,40 @@ challengeType: 11
videoId: YIqgrNLAZkA
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
```yml
question:
text: |
About how much memory does the integer `5` consume in plain Python?
answers:
- |
32 bits
- |
20 bytes
- |
16 bytes
- |
8 bits
solution: 2
```
## --text--
About how much memory does the integer `5` consume in plain Python?
## --answers--
32 bits
---
20 bytes
---
16 bytes
---
8 bits
## --video-solution--
2
# --hints--
# --solutions--
</section>

66
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-operations.md
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@ -4,41 +4,47 @@ challengeType: 11
videoId: eqSVcJbaPdk
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-numpy-6c285b74)
<section id='tests'>
# --question--
````yml
question:
text: |
What is the value of `a` after you run the following code?
## --text--
```py
a = np.arange(5)
a + 20
```
What is the value of `a` after you run the following code?
answers:
- |
```python
[20, 21, 22, 24, 24]
```
- |
```python
[0, 1, 2, 3, 4]
```
- |
```python
[25, 26, 27, 28, 29]
```
solution: 2
````
```py
a = np.arange(5)
a + 20
```
## --answers--
```python
[20, 21, 22, 24, 24]
```
---
```python
[0, 1, 2, 3, 4]
```
---
```python
[25, 26, 27, 28, 29]
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

106
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@ -4,64 +4,70 @@ challengeType: 11
videoId: BFlH0fN5xRQ
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
What will the following code print out?
certificates_earned = pd.DataFrame({
'Certificates': [8, 2, 5, 6],
'Time (in months)': [16, 5, 9, 12]
})
names = ['Tom', 'Kris', 'Ahmad', 'Beau']
```py
import pandas as pd
certificates_earned.index = names
longest_streak = pd.Series([13, 11, 9, 7], index=names)
certificates_earned['Longest streak'] = longest_streak
certificates_earned = pd.DataFrame({
'Certificates': [8, 2, 5, 6],
'Time (in months)': [16, 5, 9, 12]
})
names = ['Tom', 'Kris', 'Ahmad', 'Beau']
print(certificates_earned)
```
certificates_earned.index = names
longest_streak = pd.Series([13, 11, 9, 7], index=names)
certificates_earned['Longest streak'] = longest_streak
answers:
- |
```
Tom 13
Kris 11
Ahmad 9
Beau 7
Name: Longest streak, dtype: int64
```
- |
```
Certificates Time (in months) Longest streak
Tom 8 16 13
Kris 2 5 11
Ahmad 5 9 9
Beau 6 12 7
```
- |
```
Certificates Longest streak
Tom 8 13
Kris 2 11
Ahmad 5 9
Beau 6 7
```
solution: 2
````
print(certificates_earned)
```
## --answers--
```
Tom 13
Kris 11
Ahmad 9
Beau 7
Name: Longest streak, dtype: int64
```
---
```
Certificates Time (in months) Longest streak
Tom 8 16 13
Kris 2 5 11
Ahmad 5 9 9
Beau 6 12 7
```
---
```
Certificates Longest streak
Tom 8 13
Kris 2 11
Ahmad 5 9
Beau 6 7
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

86
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@ -4,51 +4,57 @@ challengeType: 11
videoId: _sSo2XZoB3E
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b)
<section id='tests'>
# --question--
````yml
question:
text: |
What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?
## --text--
```
Certificates Time (in months) Certificates per month
Tom 8 16 0.50
Kris 2 5 0.40
Ahmad 5 9 0.56
Beau 6 12 0.50
```
What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?
answers:
- |
```py
certificates_earned['Certificates'] /
certificates_earned['Time (in months)']
```
- |
```py
certificates_earned['Certificates per month'] = round(
certificates_earned['Certificates'] /
certificates_earned['Time (in months)']
)
```
- |
```py
certificates_earned['Certificates per month'] = round(
certificates_earned['Certificates'] /
certificates_earned['Time (in months)'], 2
)
```
solution: 3
````
```
Certificates Time (in months) Certificates per month
Tom 8 16 0.50
Kris 2 5 0.40
Ahmad 5 9 0.56
Beau 6 12 0.50
```
## --answers--
```py
certificates_earned['Certificates'] /
certificates_earned['Time (in months)']
```
---
```py
certificates_earned['Certificates per month'] = round(
certificates_earned['Certificates'] /
certificates_earned['Time (in months)']
)
```
---
```py
certificates_earned['Certificates per month'] = round(
certificates_earned['Certificates'] /
certificates_earned['Time (in months)'], 2
)
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

92
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@ -4,57 +4,63 @@ challengeType: 11
videoId: 7SgFBYXaiH0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
What will the following code print out?
certificates_earned = pd.DataFrame({
'Certificates': [8, 2, 5, 6],
'Time (in months)': [16, 5, 9, 12]
})
```py
import pandas as pd
certificates_earned.index = ['Tom', 'Kris', 'Ahmad', 'Beau']
certificates_earned = pd.DataFrame({
'Certificates': [8, 2, 5, 6],
'Time (in months)': [16, 5, 9, 12]
})
print(certificates_earned.iloc[2])
```
certificates_earned.index = ['Tom', 'Kris', 'Ahmad', 'Beau']
answers:
- |
```
Tom 16
Kris 5
Ahmad 9
Beau 12
Name: Time (in months), dtype: int64
```
- |
```
Certificates 6
Time (in months) 12
Name: Beau, dtype: int64
```
- |
```
Certificates 5
Time (in months) 9
Name: Ahmad, dtype: int64
```
solution: 3
````
print(certificates_earned.iloc[2])
```
## --answers--
```
Tom 16
Kris 5
Ahmad 9
Beau 12
Name: Time (in months), dtype: int64
```
---
```
Certificates 6
Time (in months) 12
Name: Beau, dtype: int64
```
---
```
Certificates 5
Time (in months) 9
Name: Ahmad, dtype: int64
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

94
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@ -1,59 +1,65 @@
---
id: 5e9a093a74c4063ca6f7c159
challengeType: 11
videoId: -ZOrgV_aA9A
videoId: '-ZOrgV_aA9A'
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
What will the following code print out?
certificates_earned = pd.Series(
[8, 2, 5, 6],
index=['Tom', 'Kris', 'Ahmad', 'Beau']
)
```py
import pandas as pd
print(certificates_earned[certificates_earned > 5])
```
certificates_earned = pd.Series(
[8, 2, 5, 6],
index=['Tom', 'Kris', 'Ahmad', 'Beau']
)
answers:
- |
```
Tom True
Kris False
Ahmad False
Beau True
dtype: int64
```
- |
```
Tom 8
Ahmad 5
Beau 6
dtype: int64
```
- |
```
Tom 8
Beau 6
dtype: int64
```
solution: 3
````
print(certificates_earned[certificates_earned > 5])
```
## --answers--
```
Tom True
Kris False
Ahmad False
Beau True
dtype: int64
```
---
```
Tom 8
Ahmad 5
Beau 6
dtype: int64
```
---
```
Tom 8
Beau 6
dtype: int64
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

98
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@ -4,59 +4,65 @@ challengeType: 11
videoId: 0xACW-8cZU0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/freecodecamp-intro-to-pandas-902ae59b)
<section id='tests'>
# --question--
````yml
question:
text: |
What will the following code print out?
## --text--
```py
import pandas as pd
What will the following code print out?
certificates_earned = pd.Series(
[8, 2, 5, 6],
index=['Tom', 'Kris', 'Ahmad', 'Beau']
)
```py
import pandas as pd
print(certificates_earned)
```
certificates_earned = pd.Series(
[8, 2, 5, 6],
index=['Tom', 'Kris', 'Ahmad', 'Beau']
)
answers:
- |
```
Tom 8
Kris 2
Ahmad 5
Beau 6
dtype: int64
```
- |
```
Kris 2
Ahmad 5
Beau 6
Tom 8
dtype: int64
```
- |
```
Tom 8
Kris 2
Ahmad 5
Beau 6
Name: certificates_earned dtype: int64
```
solution: 1
````
print(certificates_earned)
```
## --answers--
```
Tom 8
Kris 2
Ahmad 5
Beau 6
dtype: int64
```
---
```
Kris 2
Ahmad 5
Beau 6
Tom 8
dtype: int64
```
---
```
Tom 8
Kris 2
Ahmad 5
Beau 6
Name: certificates_earned dtype: int64
```
## --video-solution--
1
# --hints--
# --solutions--
</section>

62
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View File

@ -4,34 +4,46 @@ challengeType: 11
videoId: bJaqnTWQmb0
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b" target='_blank'>Reading SQL</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73" target='_blank'>Reading HTML</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973" target='_blank'>Reading Excel files</a>
</section>
## Tests
\- [Reading CSVs Notebook](https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46)
<section id='tests'>
\- [Reading SQL](https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b)
```yml
question:
text: |
What Python library has the `.read_html()` method we can we use for parsing HTML documents and extracting tables?
answers:
- |
BeautifierSoupy
- |
WebReader
- |
HTTP-master
- |
Pandas
solution: 4
```
\- [Reading HTML](https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73)
\- [Reading Excel files](https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973)
# --question--
## --text--
What Python library has the `.read_html()` method we can we use for parsing HTML documents and extracting tables?
## --answers--
BeautifierSoupy
---
WebReader
---
HTTP-master
---
Pandas
## --video-solution--
4
# --hints--
# --solutions--
</section>

47
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@ -4,29 +4,36 @@ challengeType: 11
videoId: NzpU17ZVlUw
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2)
<section id='tests'>
# --question--
```yml
question:
text: |
What is the main difference between lists and tuples in Python?
answers:
- |
Tuples are immutable.
- |
Lists are ordered.
- |
Tuples are unordered.
solution: 1
```
## --text--
What is the main difference between lists and tuples in Python?
## --answers--
Tuples are immutable.
---
Lists are ordered.
---
Tuples are unordered.
## --video-solution--
1
# --hints--
# --solutions--
</section>

53
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/python-introduction.md
View File

@ -4,31 +4,40 @@ challengeType: 11
videoId: PrQV9JkLhb4
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2)
<section id='tests'>
# --question--
```yml
question:
text: |
How do we define blocks of code in the body of functions in Python?
answers:
- |
We use a set of curly braces, one on either side of each new block of our code.
- |
We use indentation, usually right-aligned 4 spaces.
- |
We do not denote blocks of code.
- |
We could use curly braces or indentation to denote blocks of code.
solution: 2
```
## --text--
How do we define blocks of code in the body of functions in Python?
## --answers--
We use a set of curly braces, one on either side of each new block of our code.
---
We use indentation, usually right-aligned 4 spaces.
---
We do not denote blocks of code.
---
We could use curly braces or indentation to denote blocks of code.
## --video-solution--
2
# --hints--
# --solutions--
</section>

79
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@ -4,44 +4,53 @@ challengeType: 11
videoId: XzosGWLafrY
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2" target='_blank'>Notebook</a>
</section>
## Tests
\- [Notebook](https://notebooks.ai/rmotr-curriculum/python-under-10-minutes-15addcb2)
<section id='tests'>
# --question--
````yml
question:
text: |
How would you iterate over and print the keys and values of a dictionary named `user`?
answers:
- |
```python
for key in user.items():
print(key)
```
- |
```python
for key, value in user.all():
print(key, value)
print(value)
```
- |
```python
for key, value in user.items():
print(key, value)
```
- |
```python
for key, value in user
print(key, value)
```
solution: 3
````
## --text--
How would you iterate over and print the keys and values of a dictionary named `user`?
## --answers--
```python
for key in user.items():
print(key)
```
---
```python
for key, value in user.all():
print(key, value)
print(value)
```
---
```python
for key, value in user.items():
print(key, value)
```
---
```python
for key, value in user
print(key, value)
```
## --video-solution--
3
# --hints--
# --solutions--
</section>

86
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-csv-and-txt.md
View File

@ -4,46 +4,58 @@ challengeType: 11
videoId: ViGEv0zOzUk
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b" target='_blank'>Reading SQL</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73" target='_blank'>Reading HTML</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973" target='_blank'>Reading Excel files</a>
</section>
## Tests
\- [Reading CSVs Notebook](https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46)
<section id='tests'>
\- [Reading SQL](https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b)
````yml
question:
text: |
How would you import the CSV file `data.csv` and store it in a DataFrame using the Pandas module?
answers:
- |
```python
import pandas as pd
df = pd.csv("data.csv")
```
- |
```python
import pandas as pd
df = pd.read_csv("data.csv")
```
- |
```python
import pandas as pd
pd.read_csv("data.csv")
```
- |
```python
import pandas as pd
df = pd.csv_reader("data.csv")
```
solution: 2
````
\- [Reading HTML](https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73)
\- [Reading Excel files](https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973)
# --question--
## --text--
How would you import the CSV file `data.csv` and store it in a DataFrame using the Pandas module?
## --answers--
```python
import pandas as pd
df = pd.csv("data.csv")
```
---
```python
import pandas as pd
df = pd.read_csv("data.csv")
```
---
```python
import pandas as pd
pd.read_csv("data.csv")
```
---
```python
import pandas as pd
df = pd.csv_reader("data.csv")
```
## --video-solution--
2
# --hints--
# --solutions--
</section>

56
curriculum/challenges/chinese/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-from-databases.md
View File

@ -4,32 +4,42 @@ challengeType: 11
videoId: MtgXS1MofRw
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b" target='_blank'>Reading SQL</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73" target='_blank'>Reading HTML</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973" target='_blank'>Reading Excel files</a>
</section>
## Tests
\- [Reading CSVs Notebook](https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46)
<section id='tests'>
\- [Reading SQL](https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b)
```yml
question:
text: |
What method does a `Cursor` instance have and what does it allow?
answers:
- |
The `Cursor` instance has a `.run()` method which allows you to run SQL queries.
- |
The `Cursor` instance has a `.select()` method which allows you to select records.
- |
The `Cursor` instance has an `.execute()` method which will receive SQL parameters to run against the database.
solution: 3
```
\- [Reading HTML](https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73)
\- [Reading Excel files](https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973)
# --question--
## --text--
What method does a `Cursor` instance have and what does it allow?
## --answers--
The `Cursor` instance has a `.run()` method which allows you to run SQL queries.
---
The `Cursor` instance has a `.select()` method which allows you to select records.
---
The `Cursor` instance has an `.execute()` method which will receive SQL parameters to run against the database.
## --video-solution--
3
# --hints--
# --solutions--
</section>

101
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View File

@ -4,66 +4,75 @@ challengeType: 11
videoId: cDnt02BcHng
---
## Description
# --description--
<section id='description'>
More resources:
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46" target='_blank'>Reading CSVs Notebook</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b" target='_blank'>Reading SQL</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73" target='_blank'>Reading HTML</a>
- <a href="https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973" target='_blank'>Reading Excel files</a>
</section>
## Tests
\- [Reading CSVs Notebook](https://notebooks.ai/rmotr-curriculum/rdp-reading-csv-and-txt-files-fb829f46)
<section id='tests'>
\- [Reading SQL](https://notebooks.ai/rmotr-curriculum/rdp-reading-data-from-relational-databases-2a3a889b)
````yml
question:
text: |
Given a file named `certificates.csv` with these contents:
\- [Reading HTML](https://notebooks.ai/rmotr-curriculum/rdp-reading-html-tables-eb9cca73)
```
Name$Certificates$Time (in months)
Tom$8$16
Kris$2$5
Ahmad$5$9
Beau$6$12
```
\- [Reading Excel files](https://notebooks.ai/rmotr-curriculum/rdp-reading-excel-files-a6b99973)
Fill in the blanks for the missing arguments below:
# --question--
```py
import csv
## --text--
with open(__A__, 'r') as fp:
reader = csv.reader(fp, delimiter=__B__)
next(reader)
for index, values in enumerate(reader):
name, certs_num, months_num = values
print(f"{name} earned {__C__} certificates in {months_num} months")
```
Given a file named `certificates.csv` with these contents:
answers:
- |
A: `'certificates.csv'`
```
Name$Certificates$Time (in months)
Tom$8$16
Kris$2$5
Ahmad$5$9
Beau$6$12
```
B: `'-'`
Fill in the blanks for the missing arguments below:
C: `values`
- |
A: `'certificates.csv'`
```py
import csv
B: `'$'`
with open(__A__, 'r') as fp:
reader = csv.reader(fp, delimiter=__B__)
next(reader)
for index, values in enumerate(reader):
name, certs_num, months_num = values
print(f"{name} earned {__C__} certificates in {months_num} months")
```
C: `certs_num`
- |
A: `'certificates'`
## --answers--
B: `'$'`
A: `'certificates.csv'`
C: `certs_num`
solution: 2
````
B: `'-'`
C: `values`
---
A: `'certificates.csv'`
B: `'$'`
C: `certs_num`
---
A: `'certificates'`
B: `'$'`
C: `certs_num`
## --video-solution--
2
# --hints--
# --solutions--
</section>