In this post we will see how to convert Convert Pandas DataFrame to NumPy Array.
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You can convert Pandas DataFrame to Numpy Array to perform mathematical computation supported by NumPy library.
You can use DataFrame.to_numpy() to convert Pandas DataFrame to NumPy Array.
Syntax of DataFrame.to_numpy()
Dataframe.to_numpy(dtype = None, copy = False)
Parameters
dtype: Data type for target numpy array.
copy: [bool, default False] Whether to ensure that the returned value is a not a view on another array.
Return
DataFrame.to_numpy() returns NumPy.ndArray.
Example 1: Convert Pandas DataFrame to NumPy Array
Here is simple example to convert Pandas DataFrame to NumPy Array.
import pandas as pd
#Create a dataframe
df = pd.DataFrame(
[[32, 89, 47,87],
[67, 68, 69,78],
[87, 92, 56,98],
[98, 45, 76,99]],
columns=['C1', 'C2', 'C3','C4'])
print(' Original DataFrame\n----------\n', df)
#convert dataframe to numpy array
nArray = df.to_numpy()
print('-----Numpy Array-----\n',nArray)
Output
Original DataFrame
----------
C1 C2 C3 C4
0 32 89 47 87
1 67 68 69 78
2 87 92 56 98
3 98 45 76 99
-----Numpy Array-----
[[32 89 47 87]
[67 68 69 78]
[87 92 56 98]
[98 45 76 99]]
Example 2: Convert Pandas DataFrame to NumPy Array with mix dtypes
If you have dataframe with mixed dtypes, then NumPy array will be created of lowest dataTypes.
For example:
Python DataFrame with int64 qnd float64 will be convert to NumPy array of type float64
import pandas as pd
#Create a dataframe
df = pd.DataFrame(
[[32, 89.3, 47,87],
[67, 68.2, 69,78],
[87, 92.4, 56,98],
[98, 45.03, 76,99]],
columns=['C1', 'C2', 'C3','C4'])
print(' Original DataFrame\n----------\n', df)
#convert pandas dataframe to numpy array
nArray = df.to_numpy()
print('-----Numpy Array-----\n',nArray)
Output
Original DataFrame
----------
C1 C2 C3 C4
0 32 89.30 47 87
1 67 68.20 69 78
2 87 92.40 56 98
3 98 45.03 76 99
-----Numpy Array-----
[[32. 89.3 47. 87. ]
[67. 68.2 69. 78. ]
[87. 92.4 56. 98. ]
[98. 45.03 76. 99. ]]
That’s all about How to convert Pandas DataFrame to NumPy Array
