from numpy array to pandas DataFrame/Series

import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
# Creating a numpy array
a = np.arange(6, 15, 1) + 0.2
print(a.shape)
a
(9,)
array([ 6.2,  7.2,  8.2,  9.2, 10.2, 11.2, 12.2, 13.2, 14.2])
s_from_np = pd.Series(a)
s_from_np
0     6.2
1     7.2
2     8.2
3     9.2
4    10.2
5    11.2
6    12.2
7    13.2
8    14.2
dtype: float64
s_from_np.array
<PandasArray>
[6.2, 7.2, 8.2, 9.2, 10.2, 11.2, 12.2, 13.2, 14.2]
Length: 9, dtype: float64
s_from_np.to_numpy()
array([ 6.2,  7.2,  8.2,  9.2, 10.2, 11.2, 12.2, 13.2, 14.2])
s_from_list = pd.Series(['a', 'b', 'c'])
s_from_list
0    a
1    b
2    c
dtype: object
s_from_list.array
<PandasArray>
['a', 'b', 'c']
Length: 3, dtype: object
A2d = np.random.normal(size=(8, 2))
A2d.shape
(8, 2)
df_from_np = pd.DataFrame(A2d)
df_from_np.loc[3:7. :]
0 1
3 0.604053 0.419030
4 -1.416968 0.344342
5 0.331019 -0.322755
6 1.425032 1.385376
7 -0.910557 1.020370 
df_from_np
0 1
0 -1.925208 -1.376625
1 3.023642 -0.044192
2 0.471226 0.636105
3 0.604053 0.419030
4 -1.416968 0.344342
5 0.331019 -0.322755
6 1.425032 1.385376
7 -0.910557 1.020370

Changing indices

indices = list('abcdefgh')
indices
['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
df_from_np = pd.DataFrame(A2d, index=indices)
df_from_np
0 1
a -1.925208 -1.376625
b 3.023642 -0.044192
c 0.471226 0.636105
d 0.604053 0.419030
e -1.416968 0.344342
f 0.331019 -0.322755
g 1.425032 1.385376
h -0.910557 1.020370

Changing indices

indices = list('abcdefgh')
df_from_np.columns = ['firstCol']
df_from_np
ValueError: Length mismatch: Expected axis has 2 elements, new values have 1 elements
df_from_np.array
AttributeError: 'DataFrame' object has no attribute 'array'
df_from_np.to_numpy()
array([[-1.9252077 , -1.37662472],
       [ 3.02364168, -0.04419207],
       [ 0.47122622,  0.63610455],
       [ 0.60405305,  0.41903048],
       [-1.4169681 ,  0.34434206],
       [ 0.33101902, -0.32275461],
       [ 1.4250323 ,  1.38537568],
       [-0.91055686,  1.02037012]])