Python table gives NaN when initialized with series

Question

IF I am using this code:

a=array([2,2,2,3])
c=DataFrame({"A":1,
"B":Series(a),
"C":Timestamp("20130203"),
"D":array([3]*4),
"E":"Elephant"},index=["Firstyear","Secondyear","Thirdyear","Fourthyear"])
print(c)

I am getting the following output

A B C D E
Firstyear 1 NaN 2013-02-03 3 Elephant
Secondyear 1 NaN 2013-02-03 3 Elephant
Thirdyear 1 NaN 2013-02-03 3 Elephant
Fourthyear 1 NaN 2013-02-03 3 Elephant

But why is the B table giving Nan output and not the "a" array?

Answer 1

The NaN value you are getting is because you are trying to print both keys and values at a time for the series ---> a, this is turning out to be Nan :

I have done modification in the code ,this is generating the output as required :

import numpy as np

import pandas as pd

a=np.array([2,2,2,3],dtype="int")

data= ({"A":1,

"B":pd.Series(a).values,

"C":pd.Timestamp("20130203"),

"D":np.array([3]*4),

"E":"Elephant"})

df = pd.DataFrame(data, index=["Firstyear","Secondyear","Thirdyear","Fourthyear"]) 

print (df)