如何在熊猫中选择和存储大于数字的列?

Vin*_*mth 17 python pandas

我有一个带有整数列的pandas DataFrame.我想要包含大于10的数字的行.我可以通过执行以下操作来评估True或False而不是实际值:

df['ints'] = df['ints'] > 10
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我不经常使用Python,所以我会围绕这个圈子.

我花了20分钟谷歌搜索但未能找到我需要的东西....

编辑:

    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
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Max*_*axU 35

样本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
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只出现那些行 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
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满足b > 10条件的行的最小值(对于所有列)

In [82]: df[df.b > 10].min()
Out[82]:
a     5
b    11
c     9
dtype: int32
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b满足b > 10条件的行的最小值(对于列)

In [84]: df.loc[df.b > 10, 'b'].min()
Out[84]: 11
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更新:从Pandas 0.20.1开始,.ix索引器已弃用,支持更严格的.iloc和.loc索引器.