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Python 数据帧频率_Python_Pandas - Fatal编程技术网

Python 数据帧频率

Python 数据帧频率,python,pandas,Python,Pandas,我有这个数据框: source target 0 ape dog 1 ape hous 2 dog hous 3 hors dog 4 hors ape 5 dog ape 6 ape bird 7 ape hous 8 bird hous 9 bird fist 10 bird ape 11 fist ape 我正在尝试使用以下代码生成频率计数: df_

我有这个数据框:

source target
0     ape    dog
1     ape   hous
2     dog   hous
3    hors    dog
4    hors    ape
5     dog    ape
6     ape   bird
7     ape   hous
8    bird   hous
9    bird   fist
10   bird    ape
11   fist    ape
我正在尝试使用以下代码生成频率计数:

df_count =df.groupby(['source', 'target']).size().reset_index().sort_values(0, ascending=False)
df_count.columns = ['source', 'target', 'weight']
我得到下面的结果

source target  weight
2     ape   hous       2
0     ape   bird       1
1     ape    dog       1
3    bird    ape       1
4    bird   fist       1
5    bird   hous       1
6     dog    ape       1
7     dog   hous       1
8    fist    ape       1
9    hors    ape       1
10   hors    dog       1

我如何修改代码以使方向无关紧要,即,我得到的不是
ape bird 1
bird ape 1
,而是
ape bird 2

您可以首先按
应用
按行排序,然后将参数
名称添加到:


首先按行对值进行排序

In [31]: df
Out[31]:
   source target
0     ape    dog
1     ape   hous
2     dog   hous
3    hors    dog
4    hors    ape
5     dog    ape
6     ape   bird
7     ape   hous
8    bird   hous
9    bird   fist
10   bird    ape
11   fist    ape

In [32]: df.values.sort()

In [33]: df
Out[33]:
   source target
0     ape    dog
1     ape   hous
2     dog   hous
3     dog   hors
4     ape   hors
5     ape    dog
6     ape   bird
7     ape   hous
8    bird   hous
9    bird   fist
10    ape   bird
11    ape   fist
然后,
groupby
source,target
上,按大小进行聚合,
对结果进行排序

In [34]: df.groupby(['source', 'target']).size().sort_values(ascending=False)
    ...:   .reset_index(name='weight')
Out[34]:
  source target  weight
0    ape   hous       2
1    ape    dog       2
2    ape   bird       2
3    dog   hous       1
4    dog   hors       1
5   bird   hous       1
6   bird   fist       1
7    ape   hors       1
8    ape   fist       1

最简单的方法是对行进行排序,以便只出现一个顺序。
In [34]: df.groupby(['source', 'target']).size().sort_values(ascending=False)
    ...:   .reset_index(name='weight')
Out[34]:
  source target  weight
0    ape   hous       2
1    ape    dog       2
2    ape   bird       2
3    dog   hous       1
4    dog   hors       1
5   bird   hous       1
6   bird   fist       1
7    ape   hors       1
8    ape   fist       1