计算多列中每个唯一行的字符串出现次数

Question

我想计算多列中某些字符串的出现次数，并在新列中返回总计数

所以我知道我可以使用 value_counts 来计算给定列中值的总出现次数：

data['col'].value_counts(dropna=False)

结果：

[["win" TKO technical knockout]     336
[["win" UD unanimous decision]      307
[["win" KO knockout]                225
[["loss" UD unanimous decision]      97
[["loss" TKO technical knockout]     64
[["win" nan null]                    53
[["draw" MD majority decision]       43
[["loss" KO knockout]                41
[["loss" MD majority decision]       35
[["loss" nan null]                   32
[["loss" SD split decision]          29
[["unknown" nan null]                29
[["win" SD split decision]           27
[["draw" PTS null]                   18
[["win" RTD corner retirement]       17
[["draw" SD split decision]          12
[["loss" RTD corner retirement]      11
[["win" MD majority decision]         9
[["loss" DQ disqualification]         6
[["win" PTS null]                     6
[["unknown" NC null]                  3

问题是我想例如计算每个相关列中 [["win" KO knockout] 的出现次数（相关列是 col1 到 col20）。

这是我的数据示例：

{'col1': {0: ['["win" UD unanimous decision'],
  1: ['["win" UD unanimous decision'],
  2: ['["win" TKO technical knockout'],
  3: ['["win" UD unanimous decision'],
  4: ['["win" UD unanimous decision']},
 'col2': {0: ['["win" TKO technical knockout'],
  1: ['["win" TKO technical knockout'],
  2: ['["win" TKO technical knockout'],
  3: ['["win" UD unanimous decision'],
  4: ['["win" UD unanimous decision']},
 'col3': {0: ['["win" TKO technical knockout'],
  1: ['["win" KO knockout'],
  2: ['["win" TKO technical knockout'],
  3: ['["win" TKO technical knockout'],
  4: ['["win" UD unanimous decision']},
 'col4': {0: ['["win" UD unanimous decision'],
  1: ['["win" UD unanimous decision'],
  2: ['["win" KO knockout'],
  3: ['["win" TKO technical knockout'],
  4: ['["win" UD unanimous decision']}}

在这种情况下，所需的 output 将是：

      win UD   win TKO   win KO 
0       2         2         0
1       2         1         1
2       0         3         1
3       2         2         0
4       4         0         0

更新：

我也尝试过使用 size 和 groupby：

#list of column names
col_outcome = ['col'+str(i) for i in range(1,11)]
data.groupby(col_outcome).size()

但是，这会返回此错误消息：

类型错误：不可散列类型：“列表”

Answer 1

IIUC，让我们用stack将“宽” dataframe 重塑为“长”，然后进行一些数据字符串清理，然后使用正则表达式extract和replace ，下一个groupby并apply value_count ，最后使用unstack重塑结果：

df.stack().str[0].str.replace('\[|\"','')\
  .str.extract('(\w+\s\w+)')\
  .groupby(level=0)[0].apply(pd.Series.value_counts).unstack(fill_value=0)

Output：

   win KO  win TKO  win UD
0       0        2       2
1       1        1       2
2       1        3       0
3       0        2       2
4       0        0       4