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. Product_Id_Y 1159730 Count 1 Name: 6159402...
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
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