Extracting 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']
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?
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Can you show an example using a list of dictionaries instead of a list of lists?
How can I extract multiple columns at once from the CSV data?
What if some rows are missing the "name" value?
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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']
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?
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