In [1]:

    

import numpy as np
import pandas as pd


    

In [2]:

    

a = np.arange(4)
print(a)


    

    




[0 1 2 3]

In [3]:

    

s = pd.Series(a)
print(s)


    

    




0    0
1    1
2    2
3    3
dtype: int64

In [4]:

    

index = ['A', 'B', 'C', 'D']
name = 'sample'
s = pd.Series(data=a, index=index, name=name, dtype='float')
print(s)


    

    




A    0.0
B    1.0
C    2.0
D    3.0
Name: sample, dtype: float64

In [5]:

    

a = np.arange(12).reshape((4, 3))
print(a)


    

    




[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]]

In [6]:

    

# s = pd.Series(a)
# print(s)
# Exception: Data must be 1-dimensional


    

In [7]:

    

s = pd.Series(a[2])
print(s)


    

    




0    6
1    7
2    8
dtype: int64

In [8]:

    

s = pd.Series(a.T[2])
print(s)


    

    




0     2
1     5
2     8
3    11
dtype: int64

In [9]:

    

a = np.arange(12).reshape((4, 3))
print(a)


    

    




[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]]

In [10]:

    

df = pd.DataFrame(a)
print(df)


    

    




   0   1   2
0  0   1   2
1  3   4   5
2  6   7   8
3  9  10  11

In [11]:

    

index = ['A', 'B', 'C', 'D']
columns = ['a', 'b', 'c']
df = pd.DataFrame(data=a, index=index, columns=columns, dtype='float')
print(df)


    

    




     a     b     c
A  0.0   1.0   2.0
B  3.0   4.0   5.0
C  6.0   7.0   8.0
D  9.0  10.0  11.0