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Create a DataFrame from a Numpy array and specify the index column and column headers

  • Last Updated : 28 Jul, 2020

Let us see how to create a DataFrame from a Numpy array. We will also learn how to specify the index and the column headers of the DataFrame.

Approach :

  1. Import the Pandas and Numpy modules.
  2. Create a Numpy array.
  3. Create list of index values and column values for the DataFrame.
  4. Create the DataFrame.
  5. Display the DataFrame.

Example 1 :




# importiong the modules
import pandas as pd
import numpy as np
  
# creating the Numpy array
array = np.array([[1, 1, 1], [2, 4, 8], [3, 9, 27], 
                  [4, 16, 64], [5, 25, 125], [6, 36, 216], 
                  [7, 49, 343]])
  
# creating a list of index names
index_values = ['first', 'second', 'third',
                'fourth', 'fifth', 'sixth', 'seventh']
   
# creating a list of column names
column_values = ['number', 'squares', 'cubes']
  
# creating the dataframe
df = pd.DataFrame(data = array, 
                  index = index_values, 
                  columns = column_values)
  
# displaying the dataframe
print(df)

Output :

Example 2 :




# importiong the modules
import pandas as pd
import numpy as np
  
# creating the Numpy array
array = np.array([['Aditya', 20], ['Samruddhi', 15],
                  ['Rohan', 21], ['Anantha', 20], 
                  ['Abhinandan', 21]])
  
# creating a list of index names
index_values = ['A', 'B', 'C', 'D', 'E']
   
# creating a list of column names
column_values = ['Names', 'Age']
  
# creating the dataframe
df = pd.DataFrame(data = array, 
                  index = index_values, 
                  columns = column_values)
  
# displaying the dataframe
print(df)

Output :

Example 3 :




# importiong the modules
import pandas as pd
import numpy as np
  
# creating the Numpy array
array = np.array([['CEO', 20, 5], ['CTO', 22, 4.5], 
                  ['CFO', 21, 3], ['CMO', 24, 2]])
  
# creating a list of index names
index_values = [1, 2, 3, 4]
   
# creating a list of column names
column_values = ['Names', 'Age'
                 'Net worth in Millions']
  
# creating the dataframe
df = pd.DataFrame(data = array, 
                  index = index_values, 
                  columns = column_values)
  
# displaying the dataframe
print(df)

Output :


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