How do I select and store columns greater than a number in pandas?

Question

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 

Answer 1

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 

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