* 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 |
---|---|---|---|---|
5e9a093a74c4063ca6f7c161 | Reading Data Introduction | 11 | cDnt02BcHng | reading-data-introduction |
--description--
Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.
More resources:
--question--
--text--
Given a file named certificates.csv
with these contents:
Name$Certificates$Time (in months) Tom$8$16 Kris$2$5 Ahmad$5$9 Beau$6$12
Fill in the blanks for the missing arguments below:
import csv
with open(__A__, 'r') as fp:
reader = csv.reader(fp, delimiter=__B__)
next(reader)
for index, values in enumerate(reader):
name, certs_num, months_num = values
print(f"{name} earned {__C__} certificates in {months_num} months")
--answers--
A: 'certificates.csv'
B: '-'
C: values
A: 'certificates.csv'
B: '$'
C: certs_num
A: 'certificates'
B: '$'
C: certs_num
--video-solution--
2