如何标记DataFrame中dataType列里data3的首次连续出现

原始DataFrame #

import pandas as pd
import numpy as np

# 构造原始数据
data = {
    'position': [1,2,3,4,5,6,7,8,9,10,1,2,3,4],
    'parent': [0,1,2,2,2,2,2,2,2,2,0,0,2,3],
    'dataType': ['data1','data2','data3','data3','data3','data3','data3','data3','data3','data3','data1','data2','data4','data3'],
    'value': ['7x13124','x21312','x312','x321r','x324','xg4352','x2312','x2131','x31231','x3x3412','432-x424','x42342-0','423','x4234']
}
df = pd.DataFrame(data, index=[1,2,3,4,5,6,7,8,9,10,12,13,14,15])

核心代码 #

# 标记是否为data3
df['is_data3'] = df['dataType'] == 'data3'

# 生成连续块的编号
df['block'] = (df['is_data3'] != df['is_data3'].shift()).cumsum()

# 标记trackData3列：仅每个连续data3块的第一行为yes，其余为no
df['trackData3'] = np.where(
    df['is_data3'] & (df.groupby('block').cumcount() == 0),
    'yes',
    'no'
)

# 可选：删除中间辅助列
df = df.drop(['is_data3', 'block'], axis=1)

最终结果 #

position  parent dataType       value trackData3
1          1       0    data1    7x13124         no
2          2       1    data2     x21312         no
3          3       2    data3       x312        yes
4          4       2    data3      x321r         no
5          5       2    data3       x324         no
6          6       2    data3     xg4352         no
7          7       2    data3      x2312         no
8          8       2    data3      x2131         no
9          9       2    data3     x31231         no
10        10       2    data3    x3x3412         no
12         1       0    data1  432-x424         no
13         2       0    data2  x42342-0         no
14         3       2    data4        423         no
15         4       3    data3      x4234        yes

代码说明 #

• df['is_data3']：生成布尔列，快速筛选出所有dataType为data3的行
• df['block']：通过对比当前行与上一行的is_data3值，生成连续块的唯一编号，每个连续的相同状态（是/不是data3）会被分配同一个编号
• df.groupby('block').cumcount()：对每个块内的行进行计数，从0开始，因此每个块的第一行计数为0，结合is_data3的判断，就能精准标记每个连续data3块的起始行

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