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1.0) head Function Define and implement this function in data_utils.py. Purpose: Produce a new column-based (e.g. dict[str, list[str]]) table with only the first n (a parameter) rows of data for each column. Why: Visualizing a table with hundreds, thousands, or millions of rows in it is overwhelming. You frequently want to just see the first few rows of a table to get a sense you are on che correct path. • Function name: head Parameters: 1. dict[str, list[str]]-a column-based table of data that will not be mutated 2. int - The number of "rows" to include in the resulting list • Return type: dict[str, list[str]] mplementation strategy: 1. Establish an empty dictionary that will serve as the returned dictionary this function is building up. 2. Loop through each of the columns in the first row of the table given as a parameter. 1. Inside of the loop, establish an empty list to store each of the first N values in the column. 2. Loop through the first N items of the table's column, 1. Appending each item to the previously list established in step 2.1. 3. Assign the produced list of column values to the dictionary established in step 1. 2 Doturn tho dietio

1.0) head Function Define and implement this function in data_utils.py. Purpose: Produce a new column-based (e.g. dict[str, list[str]]) table with only the first n (a parameter) rows of data for each column. Why: Visualizing a table with hundreds, thousands, or millions of rows in it is overwhelming. You frequently want to just see the first few rows of a table to get a sense you are on che correct path. • Function name: head Parameters: 1. dict[str, list[str]]-a column-based table of data that will not be mutated 2. int - The number of "rows" to include in the resulting list • Return type: dict[str, list[str]] mplementation strategy: 1. Establish an empty dictionary that will serve as the returned dictionary this function is building up. 2. Loop through each of the columns in the first row of the table given as a parameter. 1. Inside of the loop, establish an empty list to store each of the first N values in the column. 2. Loop through the first N items of the table's column, 1. Appending each item to the previously list established in step 2.1. 3. Assign the produced list of column values to the dictionary established in step 1. 2 Doturn tho dietio

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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1.0) head Function Define and implement this function in data_utils.py. Purpose: Produce a new column-based (e.g. dict[str, list[str]1) table with only the first N (a parameter) rows of data for each column. Why: Visualizing a table with hundreds, thousands, or millions of rows in it is overwhelming. You frequently want to just see the first few rows of a table to get a sense you are on the correct path. Function name: head Parameters: 1. dict[str, list[str]]-a column-based table of data that will not be mutated 2. int - The number of "rows" to include in the resulting list • Return type: dict[str, list[str]] Implementation strategy: 1. Establish an empty dictionary that will serve as the returned dictionary this function is building up. 2. Loop through each of the columns in the first row of the table given as a parameter. 1. Inside of the loop, establish an empty list to store each of the first N values in the column. 2. Loop through the first N items of the table's column, 1. Appending each item to the previously list established in step 2.1. 3. Assign the produced list of column values to the dictionary established in step 1. 3. Return the dictionary.
Transcribed Image Text:1.0) head Function Define and implement this function in data_utils.py. Purpose: Produce a new column-based (e.g. dict[str, list[str]1) table with only the first N (a parameter) rows of data for each column. Why: Visualizing a table with hundreds, thousands, or millions of rows in it is overwhelming. You frequently want to just see the first few rows of a table to get a sense you are on the correct path. Function name: head Parameters: 1. dict[str, list[str]]-a column-based table of data that will not be mutated 2. int - The number of "rows" to include in the resulting list • Return type: dict[str, list[str]] Implementation strategy: 1. Establish an empty dictionary that will serve as the returned dictionary this function is building up. 2. Loop through each of the columns in the first row of the table given as a parameter. 1. Inside of the loop, establish an empty list to store each of the first N values in the column. 2. Loop through the first N items of the table's column, 1. Appending each item to the previously list established in step 2.1. 3. Assign the produced list of column values to the dictionary established in step 1. 3. Return the dictionary.
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