Example 1: 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
Example 2: 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 3: dataframe object to numpy array
import pandas as pd
df = pd.DataFrame(
[[21, 72, 67],
[23, 78, 69],
[32, 74, 56],
[52, 54, 76]],
columns=['a', 'b', 'c'])
arr = df.to_numpy()
print('\nNumpy Array\n----------\n', arr)
Example 4: convert dataframe to numpy array
>>> pd.DataFrame({"A": [1, 2], "B": [3, 4]}).to_numpy()
array([[1, 3],
[2, 4]])
Example 5: 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)