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Hello! I am currently self-taught pandas library using python right now, but I can not figure out the attached question.   This is the link that I found this problem, so if you needed, feel free to look it up! Thank you in advance.

Hello! I am currently self-taught pandas library using python right now, but I can not figure out the attached question.   This is the link that I found this problem, so if you needed, feel free to look it up! Thank you in advance.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Hello! I am currently self-taught pandas library using python right now, but I can not figure out the attached question.
 
This is the link that I found this problem, so if you needed, feel free to look it up! Thank you in advance.


https://datascienceinpractice.github.io/assignments/D2_Pandas.html

## Q6a: Slicing The concept of slicing can be combined with conditionals. For example, you can return all rows of a particular value. Using `value_counts()` above on the `fruity_choco` column we created, we see that there is one candy that is both chocolate and fruity in our dataset. Let’s figure out which candy that was! Use slicing to return the row from `df` where `fruity_choco` indicated the candy was both fruity and chocolate. Store this DataFrame (which will have a single row) as `both`. Again using indexing, store the name of the candy that is both fruity and chocolate in the variable `candy_name`. ```python # YOUR CODE HERE raise NotImplementedError() ``` ```python assert type(both) == pd.DataFrame assert both.shape == (1, 10) assert isinstance(candy_name, str) ```
Transcribed Image Text:## Q6a: Slicing The concept of slicing can be combined with conditionals. For example, you can return all rows of a particular value. Using `value_counts()` above on the `fruity_choco` column we created, we see that there is one candy that is both chocolate and fruity in our dataset. Let’s figure out which candy that was! Use slicing to return the row from `df` where `fruity_choco` indicated the candy was both fruity and chocolate. Store this DataFrame (which will have a single row) as `both`. Again using indexing, store the name of the candy that is both fruity and chocolate in the variable `candy_name`. ```python # YOUR CODE HERE raise NotImplementedError() ``` ```python assert type(both) == pd.DataFrame assert both.shape == (1, 10) assert isinstance(candy_name, str) ```
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