how to convert pandas dataframe to numpy array code example

Example 1: convert array to dataframe python

np.random.seed(123)
e = np.random.normal(size=10)  
dataframe=pd.DataFrame(e, columns=['a']) 
print (dataframe)
          a
0 -1.085631
1  0.997345
2  0.282978
3 -1.506295
4 -0.578600
5  1.651437
6 -2.426679
7 -0.428913
8  1.265936
9 -0.866740

e_dataframe=pd.DataFrame({'a':e}) 
print (e_dataframe)
          a
0 -1.085631
1  0.997345
2  0.282978
3 -1.506295
4 -0.578600
5  1.651437
6 -2.426679
7 -0.428913
8  1.265936
9 -0.866740

Example 2: dataframe object to numpy array

import pandas as pd

#initialize a dataframe
df = pd.DataFrame(
	[[21, 72, 67],
	[23, 78, 69],
	[32, 74, 56],
	[52, 54, 76]],
	columns=['a', 'b', 'c'])

#convert dataframe to numpy array
arr = df.to_numpy()

print('\nNumpy Array\n----------\n', arr)

Example 3: convert dataframe to numpy array

>>> pd.DataFrame({"A": [1, 2], "B": [3, 4]}).to_numpy()
array([[1, 3],
       [2, 4]])

Example 4: numpy arrauy to df

numpy_data = np.array([[1, 2], [3, 4]])
df = pd.DataFrame(data=numpy_data, index=["row1", "row2"], columns=["column1", "column2"])
print(df)

Example 5: list dataframe to numpy array

df.values

array([[nan, 0.2, nan],
       [nan, nan, 0.5],
       [nan, 0.2, 0.5],
       [0.1, 0.2, nan],
       [0.1, 0.2, 0.5],
       [0.1, nan, 0.5],
       [0.1, nan, nan]])