How to convert matrix to dictionary in Python

A matrix is ​​defined by arranging the rows and columns to form an array. The values ​​of the matrix can be characters or integers. There are several ways to convert a matrix into a Python dictionary - dictionary comprehension, for loop, enumerate and zip().

Use for loops and dictionary derivation

This program uses a for loop to iterate over the length of the matrix by applying dictionary derivation. This helps convert a matrix into a dictionary.

The Chinese translation of

Example

is:

Example

In the following example, we will show converting the name values ​​of a matrix into a dictionary. The names within each section in the matrix are labeled "Name 1", "Name 2", etc., and each section is labeled "Section 1", "Section 2", etc. Finally, it converts the resulting name-value matrix into a dictionary.

def matrix_to_dict(matrix):
   dictionary = {f"Section {i+1}": {f"Name {j+1}": matrix[i][j] for j in range(len(matrix[i]))} for i in range(len(matrix))}
   return dictionary
# Matrix input using List
matrix = [['Raghav', 'Sunil', 'Kiran', 'Rajendra'], ['Pritam', 'Rahul', 'Mehak', 'Suresh'], ['Tom', 'Peter', 'Mark', 'Jessy']]
result = matrix_to_dict(matrix)
print(result)

Output

{'Section 1': {'Name 1': 'Raghav', 'Name 2': 'Sunil', 'Name 3': 'Kiran', 'Name 4': 'Rajendra'},
'Section 2': {'Name 1': 'Pritam', 'Name 2': 'Rahul', 'Name 3': 'Mehak', 'Name 4': 'Suresh'},
'Section 3': {'Name 1': 'Tom', 'Name 2': 'Peter', 'Name 3': 'Mark', 'Name 4': 'Jessy'}}

Use nested for loops

This program uses nested for loops, iterates over the lengths of rows and columns, and returns the results as dictionary data (setting rows as keys and columns as values).

The Chinese translation of

Example

is:

Example

In the following example, the program converts a matrix into a dictionary. It builds nested dictionaries by repeating rows and columns. Each matrix component has a label like "row,col" and is connected to the matching value. Matrix data is represented by a dictionary as labeled rows and columns.

def matrix_to_dict(matrix):
   dictionary = {}
   for i in range(len(matrix)):
      row_dict = {}
      for j in range(len(matrix[i])):
         row_dict[f"col {j+1}"] = matrix[i][j]
      dictionary[f"row {i+1}"] = row_dict
   return dictionary

# matrix input
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
result = matrix_to_dict(matrix)
print(result)

Output

{'row 1': {'col 1': 1, 'col 2': 2, 'col 3': 3},
'row 2': {'col 1': 4, 'col 2': 5, 'col 3': 6},
'row 3': {'col 1': 7, 'col 2': 8, 'col 3': 9}}

Using enumerations and dictionary comprehension

Programs use enumerations to track the number of iterations in a loop and to access the elements of the loop. Next, use a dictionary comprehension to format the result of the matrix.

The Chinese translation of

Example

is:

Example

In the following example, the program begins with a recursive function that is known to call itself. Using the dictionary derivation technique, it is stored in the variable dict by using the built-in method enumerate(). Then returns the variable dict to get the new conversion of the dictionary. Now create a sublist representing the matrix and store it in the variable matrix. Then use a calling function that accepts a parameter named matrix to pass its value and store it in the variable result. Finally, we print the output with the help of result.

def matrix_to_dict(matrix):
   dict = {f"row {i+1}": {f"column {j+1}": value for j, value in enumerate(row)} for i, row in enumerate(matrix)}
   return dict
# Input of Matrix
matrix = [[11, 12, 13], [40, 50, 60], [17, 18, 19],[80, 90, 100]]
# Pass the value of the matrix using the recursive function
result = matrix_to_dict(matrix)
print(result)

Output

{'row 1': {'column 1': 11, 'column 2': 12, 'column 3': 13},
'row 2': {'column 1': 40, 'column 2': 50, 'column 3': 60},
'row 3': {'column 1': 17, 'column 2': 18, 'column 3': 19},
'row 4': {'column 1': 80, 'column 2': 90, 'column 3': 100}}

Using zip() and dictionary comprehension

This program uses the zip() function to set a nested dictionary to a value and sets the data in the key by using dictionary comprehensions {}.

The Chinese translation of

Example

is:

Example

In the following example, we will use a recursive function named matrix_to_dict fun that accepts a parameter named Matrix that has a list value. Then it uses a list comprehension to store it in a variable key. Next, it constructs a dictionary of the given key pair through comprehension techniques after iterating through each row in the matrix and storing it in a dictionary of variables. Based on the row index, a key is created for each row using the pattern "SN 1", "SN 2", etc.

Continue Return dictionary , which will calculate the matrix to dictionary conversion. Now just create matrix using sublist and store it in variable matrix. Then use the calling function to pass the variable matrix and store it in the variable result. Finally, we print the output with the help of variable results.

def matrix_to_dict(matrix):
   keys = [f"Letter {j+1}" for j in range(len(matrix[0]))]
# Each key is generated using different dictionary comprehension
   dictionary = {f"SN {i+1}": {key: value for key, value in zip(keys, row)} for i, row in enumerate(matrix)}
   return dictionary
# Take input as a character matrix using List
matrix = [['A', 'B', 'C'], ['P', 'Q', 'R'], ['X', 'Y', 'Z']]
result = matrix_to_dict(matrix)
print(result)

Output

{'SN 1': {'Letter 1': 'A', 'Letter 2': 'B', 'Letter 3': 'C'},
'SN 2': {'Letter 1': 'P', 'Letter 2': 'Q', 'Letter 3': 'R'},
'SN 3': {'Letter 1': 'X', 'Letter 2': 'Y', 'Letter 3': 'Z'}}

in conclusion

We discussed various ways to convert a matrix into a dictionary. All the above outputs show different dictionary representations using integers and characters. Overall, this transformation allows for a more efficient and flexible representation of data.

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