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* added languages to prismjs * added language to code fences for python for everybody * multiline pre to python for everybody questions * multiline pre for data analysis with python * multiline pre in numpy questions * single line pre for python for everybody * single line pre for data analysis with python * single line pre for numpy * Revert "multiline pre in numpy questions" This reverts commitaf1a02cdd3. * fix unneded escaping commit suggestions from code review Co-authored-by: Shaun Hamilton <51722130+ShaunSHamilton@users.noreply.github.com> * Revert "single line pre for numpy" This reverts commit5f90981108. * revert changes to snippet that have a language * one last code fence to pre * Revert "fix unneded escaping " This reverts commit64c84a9213. * Revert "single line pre for data analysis with python" This reverts commit3bccaff753. * Revert "single line pre for python for everybody" This reverts commit03a5379062. * remove unnecessary escape Co-authored-by: Shaun Hamilton <51722130+ShaunSHamilton@users.noreply.github.com>
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id, title, challengeType, videoId, dashedName
| id | title | challengeType | videoId | dashedName |
|---|---|---|---|---|
| 5e9a093a74c4063ca6f7c159 | Pandas Indexing and Conditional Selection | 11 | -ZOrgV_aA9A | pandas-indexing-and-conditional-selection |
--description--
Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.
More resources:
--question--
--text--
What will the following code print out?
import pandas as pd
certificates_earned = pd.Series(
[8, 2, 5, 6],
index=['Tom', 'Kris', 'Ahmad', 'Beau']
)
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