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pandas series to numpy array

ser = pd.Series(pd.Categorical(['a', 'b', 'a']))
>>> ser.to_numpy()
array(['a', 'b', 'a'], dtype=object)
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convert a pandas df to a numpy array

x = df.to_numpy()
x
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panda dataframe to numpy matrix

# Imports
import numpy as np
import pandas as pd


df= pd.read_csv('/content/drive/MyDrive/Colab Notebooks/res_data/temp/file.txt', header = None, delim_whitespace=True, error_bad_lines=False).to_numpy()
df=df.astype(float)  # convert number to float for matric calculations

print(df.shape)  # .... (16, 1) initial shaope
df.resize(4, 4)

print(df)

[[ 1.  2.  3.  4.]
 [ 5.  6.  7.  8.]
 [ 9.  3.  5.  6.]
 [ 8.  9. 79.  0.]]
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