Pandas - 计算并获取列中字符串值的唯一出现次数

Question

我有一列有 800 多行，如下所示：

0                            ['Overgrow', 'Chlorophyll']
1                            ['Overgrow', 'Chlorophyll']
2                            ['Overgrow', 'Chlorophyll']
3                               ['Blaze', 'Solar Power']
4                               ['Blaze', 'Solar Power']
5                               ['Blaze', 'Solar Power']
6                               ['Torrent', 'Rain Dish']
7                               ['Torrent', 'Rain Dish']
8                               ['Torrent', 'Rain Dish']
9                            ['Shield Dust', 'Run Away']
10                                         ['Shed Skin']
11                       ['Compoundeyes', 'Tinted Lens']
12                           ['Shield Dust', 'Run Away']
13                                         ['Shed Skin']
14                                   ['Swarm', 'Sniper']
15             ['Keen Eye', 'Tangled Feet', 'Big Pecks']
16             ['Keen Eye', 'Tangled Feet', 'Big Pecks']
17             ['Keen Eye', 'Tangled Feet', 'Big Pecks']

我想要什么？

1. 我想统计每个字符串值出现的次数。
2. 我还想将唯一的字符串值排列到一个列表中。

这是我为获得第二部分所做的工作：

list_ability = df_pokemon['abilities'].tolist()
new_list = []
for i in range(0, len(list_ability)):
    m = re.findall(r"'(.*?)'", list_ability[i], re.DOTALL)
    for j in range(0, len(m)):
        new_list.append(m[j])

list1 = set(new_list)  

我可以将唯一的字符串值放入一个列表中，但是有更好的方法吗？

示例：

'过度生长' - 3

'叶绿素' - 3

'火焰' - 3

'Sheild Dust' - 2 .... 以此类推

（顺便说一下，数据框df_pokemon中的列名是'abilities'。）

Answer 1

由于值是字符串，您可以使用正则表达式并拆分将它们转换为列表，然后使用 itertools 就像评论中提到的@JonClements 一样计数，即

from collections import Counter
count  = pd.Series(df['abilities'].str.replace('[\[\]\']','').str.split(',').map(Counter).sum())

输出：

大啄木鸟 3 叶绿素 3 雨碟 3 逃跑 2 狙击手 1 太阳能 3 纠结的脚 3 有色镜片 1 火焰 3 复眼 1 敏锐的眼光 3 杂草丛生 3 蜕皮 2 盾尘2 群 1 洪流 3 数据类型：int64 数据类型：int64

仅列出唯一值然后count[count==1].index.tolist()

['Sniper', 'Tinted Lens', 'Compoundeyes', 'Swarm']

用于制作索引列表然后

count.index.tolist()

Answer 2

使用value_counts

In [1845]: counts = pd.Series(np.concatenate(df_pokemon.abilities)).value_counts()

In [1846]: counts
Out[1846]:
Rain Dish       3
Keen Eye        3
Chlorophyll     3
Blaze           3
Solar Power     3
Overgrow        3
Big Pecks       3
Tangled Feet    3
Torrent         3
Shield Dust     2
Shed Skin       2
Run Away        2
Compoundeyes    1
Swarm           1
Tinted Lens     1
Sniper          1
dtype: int64

对于独特的价值，你可以

In [1850]: counts.index.tolist()
Out[1850]:
['Rain Dish','Keen Eye', 'Chlorophyll', 'Blaze', 'Solar Power', 'Overgrow', 
 'Big Pecks', 'Tangled Feet', 'Torrent', 'Shield Dust', 'Shed Skin', 'Run Away',
 'Compoundeyes', 'Swarm', 'Tinted Lens', 'Sniper']

或者，

In [1849]: np.unique(np.concatenate(df_pokemon.abilities))
Out[1849]:
array(['Big Pecks', 'Blaze', 'Chlorophyll', 'Compoundeyes', 'Keen Eye',
       'Overgrow', 'Rain Dish', 'Run Away', 'Shed Skin', 'Shield Dust',
       'Sniper', 'Solar Power', 'Swarm', 'Tangled Feet', 'Tinted Lens',
       'Torrent'],
      dtype='|S12')

---

注意 - 如Jon's comments 中指出的，如果type(df_pokemon.abilities[0]) 不是list，则首先转换为列表

import ast
df_pokemon.abilities = df_pokemon.abilities.map(ast.literal_eval)

---

详情

In [1842]: df_pokemon
Out[1842]:
                              abilities
0               [Overgrow, Chlorophyll]
1               [Overgrow, Chlorophyll]
2               [Overgrow, Chlorophyll]
3                  [Blaze, Solar Power]
4                  [Blaze, Solar Power]
5                  [Blaze, Solar Power]
6                  [Torrent, Rain Dish]
7                  [Torrent, Rain Dish]
8                  [Torrent, Rain Dish]
9               [Shield Dust, Run Away]
10                          [Shed Skin]
11          [Compoundeyes, Tinted Lens]
12              [Shield Dust, Run Away]
13                          [Shed Skin]
14                      [Swarm, Sniper]
15  [Keen Eye, Tangled Feet, Big Pecks]
16  [Keen Eye, Tangled Feet, Big Pecks]
17  [Keen Eye, Tangled Feet, Big Pecks]

In [1843]: df_pokemon.dtypes
Out[1843]:
abilities    object
dtype: object

In [1844]: type(df_pokemon.abilities[0])
Out[1844]: list