How do I turn a Pandas DataFrame object with 1 main column into a Pandas Series with the index column from the original DataFrame

user_14599889 0
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Say I have a simple data frame as below where I set the index of this dataframe to be the time column.

E.g

import pandas as pd

df = pd.DataFrame({'time':['2021-02-20','2021-02-21','2021-02-22','2021-02-23'], 'price':[1,2,3,4]})
df.set_index('time', inplace=True)

Now this dataframe as only 1 main column (price) so I want to know the best way to take this dataframe and simply change its type to a series.

I feel like this can be done using the pandas squeeze() method however want to know if there are any other alternatives or better ways, also correct me if my method seems wrong.

E.g

# Setting the original DataFrame to a Series, since only 1 main column can use the 'column' argument
# in the squeeze method 

df = df.squeeze('columns')
` ``
pandas series dataframe python
2 Answers

I think simplier is select column like:

s = df.set_index('time')['price']

I think inplace is not good practice, check this and this.

user_29010020

df["price"] would also give you the same thing.

user_110724440
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