如何在Pandas中标记目标字符串之后的所有Series元素为True？

你可以通过两种简洁的方式实现需求：

方法一：定位目标索引后生成布尔序列 #

先找到目标值的首次出现位置，再通过索引比较生成结果：

import pandas as pd

# 原始Series
s = pd.Series({0: 'registration address-complement-insert-confirmation input',
 1: 'decision-tree first-interaction-validation options',
 2: 'decision-tree invalid-format-validation options',
 3: 'decision-tree first-interaction-validation options',
 4: 'registration address-complement-request view',
 5: 'onboarding return-start origin',
 6: 'registration address-complement-request origin',
 7: 'decision-tree identified-regex options',
 8: 'decision-tree first-interaction-validation options',
 9: 'decision-tree first-interaction-validation options'})

# 获取目标值的首次出现索引
target_index = s.eq('onboarding return-start origin').idxmax()
# 生成结果：索引大于等于目标索引的标记为True
result = pd.Series(s.index >= target_index, index=s.index)

方法二：用累积求和直接生成标记 #

这种方法更简洁，无需单独提取索引，利用累积求和的特性自动标记后续元素：

import pandas as pd

# 原始Series
s = pd.Series({0: 'registration address-complement-insert-confirmation input',
 1: 'decision-tree first-interaction-validation options',
 2: 'decision-tree invalid-format-validation options',
 3: 'decision-tree first-interaction-validation options',
 4: 'registration address-complement-request view',
 5: 'onboarding return-start origin',
 6: 'registration address-complement-request origin',
 7: 'decision-tree identified-regex options',
 8: 'decision-tree first-interaction-validation options',
 9: 'decision-tree first-interaction-validation options'})

# 先创建仅目标位置为True的掩码
target_mask = s == 'onboarding return-start origin'
# 累积求和后转布尔值，首次出现目标值后所有位置都会被标记为True
result = target_mask.cumsum().astype(bool)

两种方法都能得到你预期的布尔Series结果，方法二更适合快速实现，逻辑也更紧凑。

内容的提问来源于stack exchange，提问作者INGl0R1AM0R1