Adding New Columns
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Adding new columns is one of the most fundamental tasks when working with tabular data. You often need to expand your data structure to include additional information, such as calculated values, default settings, or results of transformations. Common use cases for adding new columns include storing results of computations, marking data with categorical labels, or preparing data for further analysis. By understanding how to add new columns, you can make your data more informative and ready for deeper exploration.
12345678910111213# Suppose you have a dictionary of lists representing a simple dataset data = { "name": ["Alice", "Bob", "Charlie"], "age": [25, 30, 35] } # To add a new column, assign a new key with a list of values data["city"] = ["New York", "Los Angeles", "Chicago"] # Now the dictionary includes the new column print(data) # Output: # {'name': ['Alice', 'Bob', 'Charlie'], 'age': [25, 30, 35], 'city': ['New York', 'Los Angeles', 'Chicago']}
1. What is the syntax for adding a new column to a dictionary?
2. Can you add a column with default values to all rows?
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Adding New Columns
Adding new columns is one of the most fundamental tasks when working with tabular data. You often need to expand your data structure to include additional information, such as calculated values, default settings, or results of transformations. Common use cases for adding new columns include storing results of computations, marking data with categorical labels, or preparing data for further analysis. By understanding how to add new columns, you can make your data more informative and ready for deeper exploration.
12345678910111213# Suppose you have a dictionary of lists representing a simple dataset data = { "name": ["Alice", "Bob", "Charlie"], "age": [25, 30, 35] } # To add a new column, assign a new key with a list of values data["city"] = ["New York", "Los Angeles", "Chicago"] # Now the dictionary includes the new column print(data) # Output: # {'name': ['Alice', 'Bob', 'Charlie'], 'age': [25, 30, 35], 'city': ['New York', 'Los Angeles', 'Chicago']}
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