In Python, how to create NumPy array from a Pandas Dataframe?

In Python, the best way to convert a Pandas Dataframe to a NumPy array is to use the method pandas.DataFrame.to_numpy() :

>>> import pandas as pd
>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]])
>>> df.to_numpy()
array([[1, 2, 3],
       [4, 5, 6]])

By default, a view is returned: any modifications made will affect the original.

>>> array = df.to_numpy()
>>> array[0,0] = -1
>>> df
   	0	1	2 
0 	-1	2	3
1	4	5	6

To get a copy, use the copy=True option:

df.to_numpy(copy=True)

In Python, the best way to convert a Pandas Dataframe to a NumPy array is to use the method pandas.DataFrame.to_numpy() :

>>> import pandas as pd
>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]])
>>> df.to_numpy()
array([[1, 2, 3],
       [4, 5, 6]])

By default, a view is returned: any modifications made will affect the original.

>>> array = df.to_numpy()
>>> array[0,0] = -1
>>> df
   	0	1	2 
0 	-1	2	3
1	4	5	6

To get a copy, use the copy=True option:

to_numpy(copy=True)

In Python, the best way to convert a Pandas Dataframe to a NumPy array is to use the method pandas.DataFrame.to_numpy() :

>>> import pandas as pd
>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]])
>>> df.to_numpy()
array([[1, 2, 3],
       [4, 5, 6]])

By default, a view is returned: any modifications made will affect the original.

>>> array = df.to_numpy()
>>> array[0,0] = -1
>>> df
   	0	1	2 
0 	-1	2	3
1	4	5	6

To get a copy, use the copy=True option:

to_numpy(copy=True)