feat(curriculum): restore seed + solution to Chinese (#40683)

* feat(tools): add seed/solution restore script

* chore(curriculum): remove empty sections' markers

* chore(curriculum): add seed + solution to Chinese

* chore: remove old formatter

* fix: update getChallenges

parse translated challenges separately, without reference to the source

* chore(curriculum): add dashedName to English

* chore(curriculum): add dashedName to Chinese

* refactor: remove unused challenge property 'name'

* fix: relax dashedName requirement

* fix: stray tag

Remove stray `pre` tag from challenge file.

Signed-off-by: nhcarrigan <nhcarrigan@gmail.com>

Co-authored-by: nhcarrigan <nhcarrigan@gmail.com>
This commit is contained in:
Oliver Eyton-Williams
2021-01-13 03:31:00 +01:00
committed by GitHub
parent 0095583028
commit ee1e8abd87
4163 changed files with 57505 additions and 10540 deletions

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c14d
challengeType: 11
videoId: nVAaxZ34khk
dashedName: data-analysis-example-a
---
# --description--
@ -36,8 +37,3 @@ How many columns the source data had before loading.
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c14e
challengeType: 11
videoId: 0kJz0q0pvgQ
dashedName: data-analysis-example-b
---
# --description--
@ -32,8 +33,3 @@ Returns the first `n` rows based on the integer argument supplied.
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c160
challengeType: 11
videoId: mHjxzFS5_Z0
dashedName: data-cleaning-and-visualizations
---
# --description--
@ -36,8 +37,3 @@ My figure will have one row, two columns, and I am going to start drawing in the
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15f
challengeType: 11
videoId: kj7QqjXhH6A
dashedName: data-cleaning-duplicates
---
# --description--
@ -32,8 +33,3 @@ contain a duplicate, where the value for the row contains either the first or se
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15d
challengeType: 11
videoId: ovYNhnltVxY
dashedName: data-cleaning-introduction
---
# --description--
@ -55,8 +56,3 @@ dtype: bool
1
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15e
challengeType: 11
videoId: sTMN_pdI6S0
dashedName: data-cleaning-with-dataframes
---
# --description--
@ -63,8 +64,3 @@ dtype: float64
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c14f
challengeType: 11
videoId: h8caJq2Bb9w
dashedName: how-to-use-jupyter-notebooks-intro
---
# --description--
@ -34,8 +35,3 @@ An Excel sheet
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c14c
challengeType: 11
videoId: VJrP2FUzKP0
dashedName: introduction-to-data-analysis
---
# --description--
@ -36,8 +37,3 @@ It's free and open source.
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c150
challengeType: 11
videoId: 5PPegAs9aLA
dashedName: jupyter-notebooks-cells
---
# --description--
@ -34,8 +35,3 @@ Raw Cells
1
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c151
challengeType: 11
videoId: k1msxD3JIxE
dashedName: jupyter-notebooks-importing-and-exporting-data
---
# --description--
@ -42,8 +43,3 @@ All of the above.
5
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c157
challengeType: 11
videoId: XAT97YLOKD8
dashedName: numpy-algebra-and-size
---
# --description--
@ -36,8 +37,3 @@ Standard Python objects take up more memory than NumPy objects; operations on Nu
4
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c154
challengeType: 11
videoId: VDYVFHBL1AM
dashedName: numpy-arrays
---
# --description--
@ -52,8 +53,3 @@ print(A[:, :2])
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c156
challengeType: 11
videoId: N1ttsMmcVMM
dashedName: numpy-boolean-arrays
---
# --description--
@ -50,8 +51,3 @@ print(a <= 3)
4
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c152
challengeType: 11
videoId: P-JjV6GBCmk
dashedName: numpy-introduction-a
---
# --description--
@ -32,8 +33,3 @@ Working with Numpy is difficult.
1
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c153
challengeType: 11
videoId: YIqgrNLAZkA
dashedName: numpy-introduction-b
---
# --description--
@ -36,8 +37,3 @@ About how much memory does the integer `5` consume in plain Python?
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c155
challengeType: 11
videoId: eqSVcJbaPdk
dashedName: numpy-operations
---
# --description--
@ -43,8 +44,3 @@ a + 20
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15b
challengeType: 11
videoId: BFlH0fN5xRQ
dashedName: pandas-conditional-selection-and-modifying-dataframes
---
# --description--
@ -66,8 +67,3 @@ Beau 6 7
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15c
challengeType: 11
videoId: _sSo2XZoB3E
dashedName: pandas-creating-columns
---
# --description--
@ -53,8 +54,3 @@ certificates_earned['Certificates per month'] = round(
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c15a
challengeType: 11
videoId: 7SgFBYXaiH0
dashedName: pandas-dataframes
---
# --description--
@ -59,8 +60,3 @@ Name: Ahmad, dtype: int64
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c159
challengeType: 11
videoId: '-ZOrgV_aA9A'
dashedName: pandas-indexing-and-conditional-selection
---
# --description--
@ -58,8 +59,3 @@ dtype: int64
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c158
challengeType: 11
videoId: 0xACW-8cZU0
dashedName: pandas-introduction
---
# --description--
@ -61,8 +62,3 @@ Name: certificates_earned dtype: int64
1
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c164
challengeType: 11
videoId: bJaqnTWQmb0
dashedName: parsing-html-and-saving-data
---
# --description--
@ -42,8 +43,3 @@ Pandas
4
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c166
challengeType: 11
videoId: NzpU17ZVlUw
dashedName: python-functions-and-collections
---
# --description--
@ -32,8 +33,3 @@ Tuples are unordered.
1
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c165
challengeType: 11
videoId: PrQV9JkLhb4
dashedName: python-introduction
---
# --description--
@ -36,8 +37,3 @@ We could use curly braces or indentation to denote blocks of code.
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c167
challengeType: 11
videoId: XzosGWLafrY
dashedName: python-iteration-and-modules
---
# --description--
@ -49,8 +50,3 @@ for key, value in user
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c162
challengeType: 11
videoId: ViGEv0zOzUk
dashedName: reading-data-csv-and-txt
---
# --description--
@ -54,8 +55,3 @@ df = pd.csv_reader("data.csv")
2
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c163
challengeType: 11
videoId: MtgXS1MofRw
dashedName: reading-data-from-databases
---
# --description--
@ -38,8 +39,3 @@ The `Cursor` instance has an `.execute()` method which will receive SQL paramete
3
# --hints--
# --solutions--

View File

@ -2,6 +2,7 @@
id: 5e9a093a74c4063ca6f7c161
challengeType: 11
videoId: cDnt02BcHng
dashedName: reading-data-introduction
---
# --description--
@ -71,8 +72,3 @@ C: `certs_num`
2
# --hints--
# --solutions--