Python Interview Questions | Python Interview Questions And Answers | Python Tutorial | Simplilearn

///Python Interview Questions | Python Interview Questions And Answers | Python Tutorial | Simplilearn

Python Interview Questions | Python Interview Questions And Answers | Python Tutorial | Simplilearn

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This video on Python Interview Questions will help you crack your next Python interview with ease. The video includes interview questions on Numbers, lists, tuples, arrays, functions, regular expressions, strings and files. We also look into concepts such as multithreading, deep copy and shallow copy, pickling and unpickling. This video also covers Python libraries such as matplotlib, pandas, numpy,scikit and the programming paradigms followed by Python. It also covers Python library interview questions, libraries such as matplotlib, pandas, numpy and scikit. This video is ideal for both beginners as well as experienced professionals who are appearing for Python programming job interviews. Learn what are the most important Python interview questions and answers and know what will set you apart in the interview process.

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By |2019-09-14T22:49:14+00:00September 14th, 2019|Python Video Tutorials|8 Comments

8 Comments

  1. Simplilearn September 14, 2019 at 10:49 pm - Reply

    Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Thanks for watching the video. Cheers!

  2. Pankaj Ipar September 14, 2019 at 10:49 pm - Reply

    Question No. 19…i tried on python console which gives me [1],[123] & ['a']…please check..

  3. Spyphy Farnsworth September 14, 2019 at 10:49 pm - Reply

    31: np.argmax(arr)

  4. Mark Meleka September 14, 2019 at 10:49 pm - Reply

    Your videos are great, thank you for making them! I did notice some errors. Right now I'm looking at Q35 at 25:43 re: Pandas DataFrames.

    The DataFrame should be set as either: `df = pd.DataFrame([['aa', 21], ['bb',16], ['cc', 50], ['dd',33]], columns=['Name', 'Age'])` or more simply as: `df = pd.DataFrame({'Name': ['aa','bb','cc','dd'], 'Age':[21,16,50,33]})`.

    Also, when indexing in DataFrames it is important to note that whether a copy or a view is returned depends on the context. See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#indexing-view-versus-copy.
    In practice, if I index into the above DataFrame with `name_column = df['Name']` and set `name_column[0] = 999` we'll see that the values for both `name_column[0]` and `df['Name'][0]` in the original DataFrame get changed.

    Using Pandas 0.22.0.

  5. Araks Stepanyan September 14, 2019 at 10:49 pm - Reply

    Thanks for the video!
    Just a quick note, at 30:00 the output should be array([[1, 2, 3], [2, 3, 4], [0, 5, 2]]).

  6. Manish Kumawat September 14, 2019 at 10:49 pm - Reply

    Can u share PPT file??

  7. fourten0410 September 14, 2019 at 10:49 pm - Reply

    Great video, thank you!

  8. Daniel Weikert September 14, 2019 at 10:49 pm - Reply

    Do you share the files?

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