python - Converting a numpy array into a dict of values mapped to rows

Python - Converting a numpy array into a dict of values mapped to rows

You can convert a numpy array into a dictionary where each row is mapped to its corresponding values using the following code:

import numpy as np # Sample numpy array array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Convert numpy array to dict result_dict = {f"row_{i+1}": values.tolist() for i, values in enumerate(array)} print(result_dict)

This will output:

{'row_1': [1, 2, 3], 'row_2': [4, 5, 6], 'row_3': [7, 8, 9]}

Here, each row is represented as a key in the dictionary, and the corresponding values are the elements of that row in the numpy array.

Examples

  1. "Python NumPy array to dictionary by rows"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary by rows dict_by_rows = {f'Row_{i+1}': row.tolist() for i, row in enumerate(numpy_array)} # Display the resulting dictionary print(dict_by_rows)
    • Description: This code snippet converts each row of a NumPy array into a list and creates a dictionary where keys are row labels (e.g., 'Row_1', 'Row_2') and values are the corresponding lists.

  2. "Python NumPy array to dictionary mapping rows"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary mapping rows dict_mapping_rows = {tuple(row): row.tolist() for row in numpy_array} # Display the resulting dictionary print(dict_mapping_rows)
    • Description: This code example converts each row of a NumPy array into a tuple and creates a dictionary where keys are tuples representing rows and values are lists containing the row values.

  3. "Python NumPy array to dictionary with row labels"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary with row labels row_labels = ['Row_1', 'Row_2'] dict_with_row_labels = {label: row.tolist() for label, row in zip(row_labels, numpy_array)} # Display the resulting dictionary print(dict_with_row_labels)
    • Description: This code snippet associates row labels with each row of a NumPy array, creating a dictionary where keys are row labels and values are lists of row values.

  4. "Python NumPy array to dictionary with index as keys"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary with index as keys dict_with_index = {i: row.tolist() for i, row in enumerate(numpy_array)} # Display the resulting dictionary print(dict_with_index)
    • Description: This code example uses the index of each row in a NumPy array as keys to create a dictionary where keys are indices and values are lists of row values.

  5. "Python NumPy array to dictionary with row numbers"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary with row numbers dict_with_row_numbers = {i+1: row.tolist() for i, row in enumerate(numpy_array)} # Display the resulting dictionary print(dict_with_row_numbers)
    • Description: This code snippet creates a dictionary where keys are row numbers (starting from 1) and values are lists of row values obtained from a NumPy array.

  6. "Python NumPy array to dictionary with custom keys"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Custom keys for the dictionary custom_keys = ['A', 'B'] # Convert NumPy array to dictionary with custom keys dict_with_custom_keys = {key: row.tolist() for key, row in zip(custom_keys, numpy_array)} # Display the resulting dictionary print(dict_with_custom_keys)
    • Description: This code example allows customization of keys by providing a list of custom keys, resulting in a dictionary where keys are custom labels and values are lists of row values.

  7. "Python NumPy array to dictionary with row sums"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary with row sums dict_with_row_sums = {i+1: {'Row': row.tolist(), 'Sum': sum(row)} for i, row in enumerate(numpy_array)} # Display the resulting dictionary print(dict_with_row_sums)
    • Description: This code snippet creates a dictionary where keys are row numbers, and values are dictionaries containing the row values and the sum of each row.

  8. "Python NumPy array to dictionary with column names"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Column names for the dictionary column_names = ['Column_A', 'Column_B', 'Column_C'] # Convert NumPy array to dictionary with column names dict_with_column_names = {col: row.tolist() for col, row in zip(column_names, numpy_array.T)} # Display the resulting dictionary print(dict_with_column_names)
    • Description: This code example uses specified column names to create a dictionary where keys are column names, and values are lists of values from the corresponding columns in a NumPy array.

  9. "Python NumPy array to dictionary with condition"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Convert NumPy array to dictionary with a condition dict_with_condition = {i+1: row.tolist() for i, row in enumerate(numpy_array) if sum(row) > 5} # Display the resulting dictionary print(dict_with_condition)
    • Description: This code snippet demonstrates how to create a dictionary by applying a condition to the rows of a NumPy array, where keys are row numbers, and values are lists of row values.

  10. "Python NumPy array to dictionary with custom mapping"

    • Code Implementation:
      import numpy as np # Sample NumPy array numpy_array = np.array([[1, 2, 3], [4, 5, 6]]) # Custom mapping for keys custom_mapping = {'Row_A': 0, 'Row_B': 1} # Convert NumPy array to dictionary with custom mapping dict_with_custom_mapping = {key: row.tolist() for key, row in custom_mapping.items()} # Display the resulting dictionary print(dict_with_custom_mapping)
    • Description: This code example provides a way to create a dictionary with custom keys by providing a custom mapping, where keys are custom labels and values are lists of row values obtained from a NumPy array.

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