Pandas如何按规则更新point列，x/y非空时后续point值按指定逻辑调整

实现思路 #

我们通过逐行遍历DataFrame维护状态变量的方式实现规则，核心逻辑是标记所有x/y非空的行，触发下一行point值复用，之后按指定步长和区间规则递加值即可。

完整可运行代码 #

import pandas as pd
import numpy as np

# 读取数据
df = pd.read_csv("data.csv")

new_points = []
# 存储上一行最终point值
prev_point = df.loc[0, 'point']
# 标记下一行是否需要复用当前point值
need_repeat = False

for idx, row in df.iterrows():
    if idx == 0:
        new_points.append(prev_point)
        # 首行x/y非空则标记下一行复用
        if not np.isnan(row['x']) or not np.isnan(row['y']):
            need_repeat = True
        continue
    
    if need_repeat:
        current_point = prev_point
        need_repeat = False
    else:
        # 按区间规则计算当前point值
        if prev_point < 0.6:
            current_point = round(prev_point + 0.1, 1)
        elif prev_point == 0.6:
            current_point = 1.1
        elif prev_point < 1.6:
            current_point = round(prev_point + 0.1, 1)
        else:
            current_point = 0.1
    
    new_points.append(current_point)
    prev_point = current_point
    
    # 检查当前行是否触发下一行复用
    if not np.isnan(row['x']) or not np.isnan(row['y']):
        need_repeat = True

# 替换原point列
df['point'] = new_points

# 输出验证
print(df)

运行上述代码得到的结果和你给出的期望输出完全一致。

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