将缺少的类别追加到行中

Question

我有一组具有某些category的id。然而，我希望每个id都有相同数量的category，可以指定为df.id.category.unique()。

例如：Input

df1 = {"id": [1,1,1,2,2,3,3,3,3],
"category": ["a","b","e","a","d","a","b","c","d"]
}
output1 = pd.DataFrame(df1)
output1
Out[57]: 
id category
0   1        a
1   1        b
2   1        e
3   2        a
4   2        d
5   3        a
6   3        b
7   3        c
8   3        d

输出应为：Output

df2 = {"id": [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3],
"category": sum([["a","b","c","d","e"] for _ in range(3)], [])}
output2 = pd.DataFrame(df2)
output2
Out[58]: 
id category
0    1        a
1    1        b
2    1        c
3    1        d
4    1        e
5    2        a
6    2        b
7    2        c
8    2        d
9    2        e
10   3        a
11   3        b
12   3        c
13   3        d
14   3        e

如果可能的话，我希望能快速优化。非常感谢！

Answer 1

使用itertools.product:

from  itertools import product
df = pd.DataFrame(product(output1['id'].unique(), output1['category'].unique()),
columns=['id','category'])

print (df)
id category
0    1        a
1    1        b
2    1        e
3    1        d
4    1        c
5    2        a
6    2        b
7    2        e
8    2        d
9    2        c
10   3        a
11   3        b
12   3        e
13   3        d
14   3        c

或MultiIndex.from_product与MultiIndex.to_frame:

df = (pd.MultiIndex.from_product([output1['id'].unique(), output1['category'].unique()], 
names=['id','category'])
.to_frame(index=False))

print (df)
id category
0    1        a
1    1        b
2    1        e
3    1        d
4    1        c
5    2        a
6    2        b
7    2        e
8    2        d
9    2        c
10   3        a
11   3        b
12   3        e
13   3        d
14   3        c

Answer 2

您可以将numpy.tile与numpy.repeat一起使用，如下所示

import numpy as np
id_col = np.repeat([1,2,3,4,5],5).reshape(-1,1)
category_col = np.tile(["a","b","c","d","e"],5).reshape(-1,1)
arr = np.hstack([id_col,category_col])
print(arr)

输出

[['1' 'a']
['1' 'b']
['1' 'c']
['1' 'd']
['1' 'e']
['2' 'a']
['2' 'b']
['2' 'c']
['2' 'd']
['2' 'e']
['3' 'a']
['3' 'b']
['3' 'c']
['3' 'd']
['3' 'e']
['4' 'a']
['4' 'b']
['4' 'c']
['4' 'd']
['4' 'e']
['5' 'a']
['5' 'b']
['5' 'c']
['5' 'd']
['5' 'e']]

Answer 3

一个选项是pyjanitor的完整函数，用于暴露丢失的行：

#pip install git+https://github.com/pyjanitor-devs/pyjanitor.git
import pandas as pd
import janitor as jn
output1.complete('id', 'category')
Out[1280]: 
id category
0    1        a
1    1        b
2    1        e
3    2        a
4    2        d
5    3        a
6    3        b
7    3        c
8    3        d
9    1        c
10   1        d
11   2        b
12   2        c
13   2        e
14   3        e