PYTHON

convert numpy array to dataframe

import numpy as np
import pandas as pd

my_array = np.array([[11,22,33],[44,55,66]])

df = pd.DataFrame(my_array, columns = ['Column_A','Column_B','Column_C'])

print(df)
print(type(df))

df to np array

df = pd.DataFrame({"A": [1, 2], "B": [3.0, 4.5]})
>>> df.to_numpy()
array([[1. , 3. ],
       [2. , 4.5]])

make pandas df from np array

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

convert a pandas df to a numpy array

x = df.to_numpy()
x

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)

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.]]