How could I get a value out of a pandas DataFrame with a shape of (1,1) without using .to_list()[0]?

I want to get a single value from a pandas DataFrame more efficiently.

This is how I do it now:

# import pandas
import pandas as pd

# set up the dataframe
df = pd.DataFrame({'col1':['a','a','b'],'col2':[10,20,20],'col3':[100.0,200.0,300.0]})

# STEP 1 - filter down to a single row with loc
row_of_interest = df.loc[(df['col1'] == 'a') & (df['col2'] > 11)]

# STEP 2 - specify the column of interest
column_and_row_of_interest = row_of_interest['col3']

# STEP 3 - get the value out of dataframe format using to_list and list indexing
value_of_interest = column_and_row_of_interest.to_list()[0]

And of course, I can do steps 1-3 in a single line of code like this:

value_of_interest = df.loc[(df['col1'] == 'a') & (df['col2'] > 11)]['col3'].to_list()[0]  

I imagine STEP 1 and STEP 2 might be unavoidable, but STEP 3 feels clunky. Is there a better way to get a value out of a DataFrame with a shape of (1,1) than using .to_list()[0] ?

>Solution :

You can do:

print(column_and_row_of_interest.squeeze())

OR:

print(column_and_row_of_interest.iat[0])

This prints:

200.0