Converting pandas.core.series.Series to dataframe with appropriate column values python

i'm running a function in which a variable is of pandas.core.series.Series type.

type of the series shown below.
<class 'pandas.core.series.Series'>
product_id_y 1159730
count 1
Name: 6159402, dtype: object

i want to convert this into a dataframe,such that, i get

product_id_y count
1159730 1

i tried doing this:

series1 = series1.to_frame()

but getting wrong result

after converting to dataframe

 6159402
product_id_y 1159730
count 1

after doing reset index i'e series1 = series1.reset_index()

 index 6159402 0 product_id_y 1159730 1 count 1

is there anny other way to do this??

2 Answers

You was very close, first to_frame and then transpose by T:

s = pd.Series([1159730, 1], index=['product_id_y','count'], name=6159402)
print (s)
product_id_y 1159730
count 1
Name: 6159402, dtype: int64
df = s.to_frame().T
print (df) product_id_y count
6159402 1159730 1

df = s.rename(None).to_frame().T
print (df) product_id_y count
0 1159730 1

Another solution with DataFrame constructor:

df = pd.DataFrame([s])
print (df) product_id_y count
6159402 1159730 1

df = pd.DataFrame([s.rename(None)])
print (df) product_id_y count
0 1159730 1

Sample:

import pandas as pd
df = pd.DataFrame({'Name': ['Will','John','John','John','Alex'], 'Payment': [15, 10, 10, 10, 15], 'Duration': [30, 15, 15, 15, 20]})

You can print by converting the series/dataframe to string:

> print (df.to_string()) Duration Name Payment
0 30 Will 15
1 15 John 10
2 15 John 10
3 15 John 10
4 20 Alex 15
> print (df.iloc[1].to_string())
Duration 15
Name John
Payment 10