pandas基于其他列创建新列

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df['C'] = df['A'] + df['B']  # 创建新列 C，其值为 A 列和 B 列的和

def custom_function(row):
    return row['A'] * 2 + row['B']

df['D'] = df.apply(custom_function, axis=1)  # 应用函数创建新列 D

df['E'] = df.apply(lambda row: 'High' if row['A'] > 2 else 'Low', axis=1)

import pandas as pd

# 创建一个示例数据框
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)

# 直接计算新列
df['C'] = df['A'] + df['B']

# 使用自定义函数计算新列
def custom_function(row):
    return row['A'] * 2 + row['B']

df['D'] = df.apply(custom_function, axis=1)

# 使用条件表达式创建新列
df['E'] = df.apply(lambda row: 'High' if row['A'] > 2 else 'Low', axis=1)

print(df)

   A  B  C   D    E
0  1  4  5   6  Low
1  2  5  7   9  Low
2  3  6  9  12  High