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我有一个数据框,其中每一行都包含一个字符串列表。我编写了一个函数,对每个字符串执行伯努利类型的试验,如果试验成功,每个单词都有一定的概率(这里为 0.5)被删除。见下文:

import numpy as np
import pandas as pd

def bernoulli_trial (sublist, prob = 0.5):

    # create mask of trial outcomes per each object in sublist
    mask = np.random.binomial(n=1, p=prob, size=len(sublist))

    # perform transformation on bernoulli successes
    transformed_sublist = [token for delete, token in zip(mask, sublist) if not delete]

    return transformed_sublist

当我传递数据帧的每一行时,这按预期工作,根据:

df = pd.DataFrame(data={'store': [1,2,3], 'colours': [['red','blue','yellow','green','brown','pink'],
                                                      ['black','white'],
                                                      ['purple','orange','cyan','mauve']]})

df['colours'] = df['colours'].apply(bernoulli_trial)

Out: 
0      [red, green]
1           [black]
2    [orange, cyan]
Name: colours, dtype: object

但是,我现在要做的不是在每个子列表和每个字符串中统一应用函数,而是对(a)给定子列表是否将传递给函数(是/否)和(b)应用条件将应用该子列表中的字符串(即通过指定我只想测试某些颜色)。

我认为我对(a)部分有一个可行的解决方案 - 通过将伯努利函数包装在一个检查是否满足给定条件的函数中(即子列表的长度是否大于 2 个对象?) - 这有效(见下文)但我不确定是否有更有效的(阅读更多pythonic)方法来做到这一点。

def sublist_condition_check(sublist):
    if len(sublist) > 2:
        sublist = bernoulli_trial(sublist)
    else:
        sublist = sublist
    return sublist

请注意,任何不满足条件的子列表应保持不变。

df['colours'].apply(sublist_condition_check)

Out: 
0      [red, brown]
1    [black, white] # this sublist had only two elements so remains unchanged
2           [mauve]
Name: colours, dtype: object

但是,我完全不知道如何对每个单词应用条件逻辑。例如,假设我只想将试验应用于预先指定的颜色列表 ['red','mauve','black'] - 前提是它通过了子列表条件检查 - 我该怎么做呢?

我希望实现的伪代码如下所示:

for sublist in df:
    if len(sublist) > 2:     # check if sublist contains more than two objects
        for colour in sublist:     # cycle through each colour within the sublist
            if colour in ['red','mauve','black']:     
                colour = bernoulli_trial (colour)     # only run bernoulli if colour in list
            else:
                colour = colour     # if colour not in list, colour remains unchanged
        else:
            sublist = sublist     # if sublist <= 2, sublist remains unchanged

我知道对此的字面解释是行不通的,因为最初的 bernoulli_trial 函数接收一个列表而不是单个字符串。但希望它描述了我想要实现的目标。

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1 回答 1

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不确定关于回答我自己的问题的礼仪,但我想我会提供一些我已经确定的工作解决方案的细节,以防有人遇到类似情况。

我已经扩展了最初的伯努利函数,以包含一个附加的 if 语句,该语句基于每个字符串是否符合包含标准。

# internal function - bernoulli trial for each string in sublist
def bernoulli_trial (sublist, prob = 0.50):

    # set token criteria for performing bernoulli trial
    token_criteria = ['red','black','purple'] # perform trial only on these strings

    # create mask of trial outcomes per each word in sublist
    mask = np.random.binomial(n=1, p=prob, size=len(turn))

    # perform transformation (deletion) on bernoulli successes
    transformed_turn = []
    for token, delete in zip(turn, mask):             
        if token not in token_criteria:
            transformed_turn.append(token)
        else:
            if delete == 0: # retain only those strings not marked for deletion
                transformed_turn.append(token)

    return transformed_sublist

结合sublist_condition_check问题中描述的功能,现在可以按预期执行

于 2020-11-21T12:38:49.390 回答