selecting value in one row of DataFrame based on value in other

Question

i have the following example DataFrame

df2 = pd.DataFrame(np.array([[5,0,-3],['nyc','sf','chi']]), columns=['col1','col2','col3'], index=['value','location'])

for this example, i want to retrieve the number in the 'value' row where the 'location' = 'nyc', so in this case, i want to retrieve the number 5. i am trying to use the .loc with a boolean but can't quite get it right

Answer 1

You may need two .loc

df2.loc['value',df2.loc['location']=='nyc']
Out[269]: 
col1    5
Name: value, dtype: object

If only need value output

df2.loc['value',df2.loc['location']=='nyc'].iloc[0]
Out[270]: '5'

Answer 2

This will get you the value in the value row, but I am indexing it using iloc instead of loc :

df2.iloc[0, np.where(df2.loc['location', ] == 'nyc')[0]].values

OUTPUT:

array(['5'], dtype=object)