如何检查pandas datafram中是否存在具有特定列值的行

2024-03-29 05:04:13 发布

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如果要提取给定行标签和列标签序列的一组值,并且lookup方法允许这样做并返回numpy数组。

以下是我的代码片段和输出:

>>> import pandas as pd
>>> import numpy as np
>>> df = DataFrame(np.random.rand(20,4), columns = ['A','B','C','D'])
>>> df
           A         B         C         D
0   0.121190  0.360813  0.500082  0.817546
1   0.304313  0.773412  0.902835  0.440485
2   0.700338  0.733342  0.196394  0.364041
3   0.385534  0.078589  0.181256  0.440475
4   0.151840  0.956841  0.422713  0.018626
5   0.995875  0.110973  0.149234  0.543029
6   0.274740  0.745955  0.420808  0.020774
7   0.305654  0.580817  0.580476  0.210345
8   0.726075  0.801743  0.562489  0.367190
9   0.567987  0.591544  0.523653  0.133099
10  0.795625  0.163556  0.594703  0.208612
11  0.977728  0.751709  0.976577  0.439014
12  0.967853  0.214956  0.126942  0.293847
13  0.189418  0.019772  0.618112  0.643358
14  0.526221  0.276373  0.947315  0.792088
15  0.714835  0.782455  0.043654  0.966490
16  0.760602  0.487120  0.747248  0.982081
17  0.050449  0.666720  0.835464  0.522671
18  0.382314  0.146728  0.666722  0.573501
19  0.392152  0.195802  0.919299  0.181929

>>> df.lookup([0,2,4,6], ['B', 'C', 'A','D'])
array([ 0.36081287,  0.19639367,  0.15184046,  0.02077381])
>>> df.lookup([0,2,4,6], ['A', 'B', 'C','D'])
array([ 0.12119047,  0.73334194,  0.4227131 ,  0.02077381])
>>>
import numpy as np
import pandas as pd
df = pd.DataFrame(data = np.arange(8).reshape(4,2), columns=['name', 'value'])

结果:

>>> df
   name  value
0     0      1
1     2      3
2     4      5
3     6      7
>>> any(df.name == 4)
True
>>> any(df.name == 5)
False

第二部分:

my_data = np.arange(8).reshape(4,2)
my_data[0,0] = 4

df = pd.DataFrame(data = my_data, columns=['name', 'value'])

结果:

>>> df.loc[df.name == 4]
   name  value
0     4      1
2     4      5

更新:

my_data = np.arange(8).reshape(4,2)
my_data[0,0] = 4

df = pd.DataFrame(data = my_data, index=['a', 'b', 'c', 'd'], columns=['name', 'value'])

结果:

>>> df.loc[df.name == 4]  # gives relevant rows
   name  value
a     4      1
c     4      5  
>>> df.loc[df.name == 4].index  # give "row names" of relevant rows
Index([u'a', u'c'], dtype=object)

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