从熊猫数据框中提取单个数据

Question

How do you extract a value (string) from a given Dataframe, given a certain value from a different column.

For example, I would like to get the 'Adrs' where 'Value'=2

import pandas as pd

df = pd.DataFrame({'Adrs':["AAA","BBB"],'Value':[1,2]}, index=[0,1])

print(df)
print("")

df2 = df[df['Value']==2]
string = df2.Adrs
print(string)

Output:

Adrs  Value
0  AAA      1
1  BBB      2

1    BBB
Name: Adrs, dtype: object

I would like to extract just the "BBB" instead of that entire table/data frame. Is there a quick way to do this without doing some parsing of the df2.Adrs

If df2 has multiple rows, I can extract BBB by df2['Adrs'][1]

see below:

import pandas as pd

df = pd.DataFrame({'Adrs':["AAA","BBB"],'Value':[2,2]}, index=[0,1])

print(df)
print("")

df2 = df[df['Value']==2]
string = str(df2['Adrs'][1])
print(string)

output:

 Adrs  Value
0  AAA      2
1  BBB      2

BBB

Answer 1

>>> df.loc[df['Value'] == 2, 'Adrs'].values[0]
'BBB'
>>> df.iat[1, 0]
'BBB'
>>> df.at[1, 'Adrs']
'BBB'

Are a few ways. I'm sure there's more.

Answer 2

df2.Adrs is still a Series, so what you want to do is grab one element from it. df2.Adrs.iloc(0) will get you the first element, regardless of indexing. But what will you do if df2 has multiple rows?