Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Learn Extracting and Transforming Data | Working with Structured Data Formats
Strings and Data Formats in Python

bookExtracting and Transforming Data

1234567891011
# Suppose you have CSV data loaded as a list of rows, where each row is a list of strings. rows = [ ["id", "name", "age", "city"], ["1", "Alice", "30", "New York"], ["2", "Bob", "25", "Los Angeles"], ["3", "Charlie", "35", "Chicago"] ] # To extract the "name" column (index 1) from all rows except the header: name_column = [row[1] for row in rows[1:]] print(name_column) # Output: ['Alice', 'Bob', 'Charlie']
copy

When working with structured data such as JSON, you often deal with a list of dictionaries, where each dictionary represents an object with key-value pairs. To extract values for a given key from all dictionaries in the list, use a list comprehension. For instance, if you have a list of dictionaries representing people and want to extract all ages, you can use [person["age"] for person in people]. This approach gives you a new list containing only the values associated with the specified key from each dictionary.

1. Which of the following is the best way to access a value for a specific key in a dictionary?

2. Which approaches can be used to extract a column from a list of lists?

question mark

Which of the following is the best way to access a value for a specific key in a dictionary?

Select the correct answer

question mark

Which approaches can be used to extract a column from a list of lists?

Select the correct answer

Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 3. ChapterΒ 3

Ask AI

expand

Ask AI

ChatGPT

Ask anything or try one of the suggested questions to begin our chat

bookExtracting and Transforming Data

Swipe to show menu

1234567891011
# Suppose you have CSV data loaded as a list of rows, where each row is a list of strings. rows = [ ["id", "name", "age", "city"], ["1", "Alice", "30", "New York"], ["2", "Bob", "25", "Los Angeles"], ["3", "Charlie", "35", "Chicago"] ] # To extract the "name" column (index 1) from all rows except the header: name_column = [row[1] for row in rows[1:]] print(name_column) # Output: ['Alice', 'Bob', 'Charlie']
copy

When working with structured data such as JSON, you often deal with a list of dictionaries, where each dictionary represents an object with key-value pairs. To extract values for a given key from all dictionaries in the list, use a list comprehension. For instance, if you have a list of dictionaries representing people and want to extract all ages, you can use [person["age"] for person in people]. This approach gives you a new list containing only the values associated with the specified key from each dictionary.

1. Which of the following is the best way to access a value for a specific key in a dictionary?

2. Which approaches can be used to extract a column from a list of lists?

question mark

Which of the following is the best way to access a value for a specific key in a dictionary?

Select the correct answer

question mark

Which approaches can be used to extract a column from a list of lists?

Select the correct answer

Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 3. ChapterΒ 3
some-alt