I am querying a single value from my data frame which seems to be \'dtype: object\'. I simply want to print the value as it is with out printing the index or other information a
If you can guarantee only one result is returned, use loc
and call item
:
>>> df.loc[df['Host'] == 'a', 'Port'].item()
'b'
Or, similarly,
>>> df.loc[df['Host'] == 'a', 'Port'].values[0]
'b'
...to get the first value (similarly, .values[1]
for the second). Which is better than df.loc[df['Host'] == 'a', 'Port'][0]
because, if your DataFrame looks like this,
Host Port
1 a b
Then "KeyError: 0" will be thrown—
df.loc[df['Host'] == 'a', 'Port'][0]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Alternatively, use at
:
>>> df.at[df['Host'].eq('a').idxmax(), 'Port']
'b'
The drawback is that if 'a' doesn't exist, idxmax
will return the first index (and return an incorrect result).
it should work simply..
>>> df
Host Port
0 a b
>>> df[df['Host'] == 'a']['Port'][0] # will choose the first index simply which is 'b'
'b'
OR, use with print which will strip off the surrounded single ticks.
>>> print(df[df['Host'] == 'a']['Port'][0])
b
This will easier because you have just choose the desired Index even if you have Multiple values across Port
columns
Example:
>>> df
Host Port
0 a b
1 c c
Looking for distinct a
& c
based on Index:
>>> df[df['Host'] == 'a']['Port'][0]
'b'
>>> df[df['Host'] == 'c']['Port'][1]
'c'
As mentioned in my comment, using [1] should work afterwards, to pull the variable you're looking for.
t = df[df['Host'] == 'a']['Port'][1]