I have a pandas DataFrame with a column of integers. I want the rows containing numbers greater than 10. I am able to evaluate True or False but not the actual value, by doing:

df['ints'] = df['ints'] > 10

I don't use Python very often so I'm going round in circles with this.

I've spent 20 minutes Googling but haven't been able to find what I need....

Edit:

    observationID   recordKey   gridReference   siteKey siteName    featureKey  startDate   endDate pTaxonVersionKey    taxonName   authority   commonName  ints
0   463166539   1767    SM90    NaN NaN 150161  12/02/2006  12/02/2006  NBNSYS0100004720    Pipistrellus pygmaeus   (Leach, 1825)   Soprano Pipistrelle 2006
1   463166623   4325    TL65    NaN NaN 168651  21/12/2008  21/12/2008  NHMSYS0020001355    Pipistrellus pipistrellus sensu stricto (Schreber, 1774)    Common Pipistrelle  2008
2   463166624   4326    TL65    NaN NaN 168651  18/01/2009  18/01/2009  NHMSYS0020001355    Pipistrellus pipistrellus sensu stricto (Schreber, 1774)    Common Pipistrelle  2009
3   463166625   4327    TL65    NaN NaN 168651  15/02/2009  15/02/2009  NHMSYS0020001355    Pipistrellus pipistrellus sensu stricto (Schreber, 1774)    Common Pipistrelle  2009
4   463166626   4328    TL65    NaN NaN 168651  19/12/2009  19/12/2009  NHMSYS0020001355    Pipistrellus pipistrellus sensu stricto (Schreber, 1774)    Common Pipistrelle  2009

Sample DF:

In [79]: df = pd.DataFrame(np.random.randint(5, 15, (10, 3)), columns=list('abc'))In [80]: df
Out[80]:a   b   c
0   6  11  11
1  14   7   8
2  13   5  11
3  13   7  11
4  13   5   9
5   5  11   9
6   9   8   6
7   5  11  10
8   8  10  14
9   7  14  13

present only those rows where b > 10

In [81]: df[df.b > 10]
Out[81]:a   b   c
0  6  11  11
5  5  11   9
7  5  11  10
9  7  14  13

Minimums (for all columns) for the rows satisfying b > 10 condition

In [82]: df[df.b > 10].min()
Out[82]:
a     5
b    11
c     9
dtype: int32

Minimum (for the b column) for the rows satisfying b > 10 condition

In [84]: df.loc[df.b > 10, 'b'].min()
Out[84]: 11

UPDATE: starting from Pandas 0.20.1 the .ix indexer is deprecated, in favor of the more strict .iloc and .loc indexers.