Pandas-DataFrame无法以副本形式保存在新的变量内

Question

data = np.random.randn(5,4)
df = pd.DataFrame(data,columns=list('ABCD'),index=[1,2,'a','b','2006-10-1'])

#尝试复制一份df的副本并命名为df_1
df_1 = df

#对副本df_1进行修改
df_1['Else'] = df_1['A']

#发现原数据帧df也被修改了
df.info()

输出情况：

<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, 1 to 2006-10-1
Data columns (total 5 columns):
 #   Column  Non-Null Count  Dtype  
---  ------  --------------  -----  
 0   A       5 non-null      float64
 1   B       5 non-null      float64
 2   C       5 non-null      float64
 3   D       5 non-null      float64
 4   Else    5 non-null      float64
dtypes: float64(5)
memory usage: 240.0+ bytes

请问如何才能保存一个新的数据帧副本，以防止原数据被修改？

Answer 1

import numpy as np
import pandas as pd
data = np.random.randn(5,4)

df = pd.DataFrame(data,columns=list('ABCD'),index=[1,2,'a','b','2006-10-1'])

#尝试复制一份df的副本并命名为df_1
df_1 = df.copy(deep=True)
 
#对副本df_1进行修改
df_1['Else'] = df_1['A']
 
df.info() 
df_1.info()