Print the raw value of a column alone, in pandas?

I have a dataframe:

df = pd.DataFrame([ { 'name': 'george', 'age': 23 }, {'name': 'anna', 'age': 26}])

Now I want to retrive George’s age:

df[df.name == 'george'].age

But this outputs some extra information along with the raw value:

0    23
Name: age, dtype: int64

How do I just get it to print 23?

Answers:

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Method 1

You can use loc + values for converting Serie to numpy array and then select first value by [0]:

print (df.loc[df.name == 'george', 'age'].values)
[23]
print (df.loc[df.name == 'george', 'age'].values[0])
23

Or simply select first value of Series with iloc:

print (df.loc[df.name == 'george', 'age'].iloc[0])
23

Or select first item by iat:

print (df.loc[df.name == 'george', 'age'].iat[0])
23

Or use Series.item:

print (df.loc[df.name == 'george', 'age'].item())
23

If possible no match value, above solutions failed.

Then is possible use next with iter trick:

print (next(iter(df.loc[df.name == 'george', 'age']),'no match value'))
23

print (next(iter(df.loc[df.name == 'jano z hornej dolnej', 'age']),'no match value'))
no match value

Method 2

Might as well make my comment an answer:

df[df.name == 'george'].age.values[0]

or

int(df[df.name == 'george'].age)

should work

Method 3

df = [ { 'name': 'george', 'age': 23 }, {'name': 'anna', 'age': 26}]
k = [x['age'] for x in df if x['name'] == 'george']
print k

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0