Pandas -比较2列并根据优先级选择值

import pandas as pd
import numpy as np

df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [5, 4, 3, 2, 1]})
priority = [2, 1, 3, 1, 2]

df['C'] = np.where(df['A'] > df['B'], df['A'], df['B'])
df['Priority'] = priority

df['Result'] = np.where(df['Priority'] == 1, df['A'], np.where(df['Priority'] == 2, df['B'], np.nan))

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [5, 4, 3, 2, 1]})
priority = [2, 1, 3, 1, 2]

def select_value(row):
    if row['A'] > row['B']:
        return row['A']
    else:
        return row['B']

df['C'] = df.apply(select_value, axis=1)
df['Priority'] = priority

def select_value_by_priority(row):
    if row['Priority'] == 1:
        return row['A']
    elif row['Priority'] == 2:
        return row['B']
    else:
        return None

df['Result'] = df.apply(select_value_by_priority, axis=1)

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [5, 4, 3, 2, 1]})
priority = [2, 1, 3, 1, 2]

df['C'] = df['A'].where(df['A'] > df['B'], df['B'])
df['Priority'] = priority

df['Result'] = df.apply(lambda row: row['A'] if row['Priority'] == 1 else row['B'] if row['Priority'] == 2 else None, axis=1)