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Mastering Data Analysis with Pandas(으)로 돌아가기

Coursera Project Network의 Mastering Data Analysis with Pandas 학습자 리뷰 및 피드백

4.6
별점
20개의 평가
4개의 리뷰

강좌 소개

In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the first of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

필터링 기준:

Mastering Data Analysis with Pandas의 4개 리뷰 중 1~4

교육 기관: Donna G

2022년 5월 13일

This guided coding project helped concrete what I've been learning in other courses. I'm really glad I took it. I think it helped boost my confidence in what I've been learning. The instructor and the material was easy to understand and informative.

교육 기관: Manny V

2022년 6월 8일

The Mastering Data Analysis with Pandas : Part 1 addresses Panda Series and sets you up perfectly for Data Frames and advanced topics.

교육 기관: ramazan y

2021년 11월 9일

a good start for new learners

교육 기관: Richard A

2022년 5월 12일

For a recent course, it includes some obsolete code:

read_csv('file', squeeze = True)

Squeeze is not supported in Pandas read_csv and must be called as

pd.read_csv('file').squeeze("columns")

Sorting has changed also:

series.sort_values(inplace=True)

is not suppoorted and needs to be done by making a copy:

series = series.sort_values()

The virtual environment is horrible - the screens are too small on a laptop, contantly timing out (I have a fast fibre connection) and the video pauses for no reason.

I downloaded the notebook to work on it in my own editor, but every time you click out of the course window, the video pauses. Very frustrating to work with.

The course could be condensed into no more than half an hour - there's a lot of time spent talking about what's going to be talked about instead of just talking about the subject in hand and then going over some basic points over and over.