NumPy: Convert Pandas dataframe to Numpy array with headers
Convert Pandas DataFrame to NumPy array with headers.
Write a NumPy program to convert Pandas dataframe to Numpy array with headers.
Sample Solution:
Python Code:
# Importing necessary libraries
import numpy as np
import pandas as pd
# Generating a 12x3 NumPy array with random values
np_array = np.random.rand(12, 3)
# Printing the original NumPy array and its type
print("Original NumPy array:")
print(np_array)
print("Type: ", type(np_array))
# Creating a Pandas DataFrame from a 12x3 NumPy array with random values and labeled columns A, B, C
df = pd.DataFrame(np.random.rand(12, 3), columns=['A', 'B', 'C'])
# Printing the Pandas DataFrame and its type
print("\nPandas DataFrame:")
print(df)
print("Type: ", type(df))
Sample Output:
Original Numpy array:
[[0.18308157 0.32258608 0.39644848]
[0.31018507 0.08220454 0.40018982]
[0.63639779 0.34908174 0.39878868]
[0.74477532 0.4250794 0.12355822]
[0.61842804 0.78525555 0.95617131]
[0.17971402 0.03450462 0.3756935 ]
[0.34533001 0.68281693 0.42670306]
[0.90444404 0.96700828 0.87172799]
[0.53261873 0.18419712 0.54780473]
[0.50476661 0.82657057 0.06935023]
[0.02482073 0.02318678 0.36032194]
[0.69001834 0.04285817 0.31768865]]
Type: <class 'numpy.ndarray'>
Panda's DataFrame:
A B C
0 0.015583 0.968431 0.943192
1 0.221607 0.704098 0.241200
2 0.466129 0.269226 0.450781
3 0.747222 0.674508 0.686070
4 0.908001 0.399580 0.124778
5 0.540362 0.024179 0.560710
6 0.572349 0.992342 0.347848
7 0.609707 0.786937 0.150088
8 0.162281 0.412158 0.761437
9 0.969180 0.215166 0.769721
10 0.272827 0.817238 0.093650
11 0.196416 0.643602 0.262683
Type: <class 'pandas.core.frame.DataFrame'>
Explanation:
np_array = np.random.rand(12,3): This line generates a 12x3 NumPy array with random values between 0 and 1 from a uniform distribution and stores in the variable np_array.
df = pd.DataFrame(np.random.rand(12,3),columns=['A','B','C']): Creates a new 12x3 pandas DataFrame ‘df’ with random values between 0 and 1 from a uniform distribution. The columns are labeled 'A', 'B', and 'C'.
Pictorial Presentation:
Python-Numpy Code Editor: