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