python - 将 Pandas 值组合到成员组中

Question

我正在尝试将两个 Pandas 列中的数字关联到成员资格组中。这是我目前所拥有的:

import pandas as pd
df = pd.DataFrame({'A':[0, 1, 3, 4, 6, 7, 8, 8, 8, 9, 9, 9, 9, 9, 11, 12, 13, 14, 15, 15, 15, 16, 16, 16, 16, 17, 17, 17, 17, 18, 18, 18, 18, 18, 19, 19, 19, 19, 20, 20, 21, 22, 24, 25, 26, 27, 28, 29, 29],
               'B':[1, 0, 4, 3, 7, 6, 112, 9, 114, 134, 135, 112, 8, 114, 14, 13, 12, 11, 16, 17, 18, 17, 15, 18, 19, 16, 18, 15, 19, 17, 16, 15, 19, 20, 20, 18, 17, 16, 19, 18, 22, 21, 25, 24, 27, 26, 29, 28, 30]})   

df = df.groupby('A')['B'].apply(lambda x: list(set(x))).reset_index()

^ 信用 jezrael

df['A']=df['A'].apply(lambda x : [x])
df_new=pd.DataFrame((df['A'] + df['B']),columns=["Combined"])
df_new["Combined"]=df_new["Combined"].sort_values().apply(lambda x: sorted(x))

将 A 列中的数字和 B 中分组的值组合并排序。

                       Combined
0                       [0, 1]
1                       [0, 1]
2                       [3, 4]
3                       [3, 4]
4                       [6, 7]
5                       [6, 7]
6             [8, 9, 112, 114]
7   [8, 9, 112, 114, 134, 135]
8                     [11, 14]
9                     [12, 13]
10                    [12, 13]
11                    [11, 14]
12            [15, 16, 17, 18]
13        [15, 16, 17, 18, 19]
14        [15, 16, 17, 18, 19]
15    [15, 16, 17, 18, 19, 20]
16        [16, 17, 18, 19, 20]
17                [18, 19, 20]
18                    [21, 22]
19                    [21, 22]
20                    [24, 25]
21                    [24, 25]
22                    [26, 27]
23                    [26, 27]
24                    [28, 29]
25                [28, 29, 30]

如何删除 df_new 中的重复列表。也许可以将列表转换为字符串值？

最重要的是，我想从原始 col_A 中获取每个值，并将其与它所属的组合列表中最具包容性的一个相关联。 因此，df 的 col_A 中的数字 8 应该与 df_new 中 Combined 列的第 7 行相关联，该行具有数字 8 的最包容列表 - [8, 9, 112, 114, 134, 135]。

谢谢你的帮助

Answer 1

我建议将您的 DataFrame 转换为 numpy 矩阵，使用 np.unique 方法获取唯一列表的矩阵，然后像这样转换回 DataFrame:

df_new["Combined"] = pd.DataFrame(np.unique(df_new.as_matrix()))

#                              0
# 0                       [0, 1]
# 1                       [3, 4]
# 2                       [6, 7]
# 3             [8, 9, 112, 114]
# 4   [8, 9, 112, 114, 134, 135]
# 5                     [11, 14]
# 6                     [12, 13]
# 7             [15, 16, 17, 18]
# 8         [15, 16, 17, 18, 19]
# 9     [15, 16, 17, 18, 19, 20]
# 10        [16, 17, 18, 19, 20]
# 11                [18, 19, 20]
# 12                    [21, 22]
# 13                    [24, 25]
# 14                    [26, 27]
# 15                    [28, 29]
# 16                [28, 29, 30]