Setting value to a dataframe using df.loc updates a copy of the dataframe

Question

import pandas as pd

#Inserting some data into name_df 

list_name = ["Al","Brad"]  
list_age = [20,30]

name_df = pd.DataFrame(list_name,columns=["name"])  
age_df = pd.DataFrame(list_age,columns=["age"])

name_df = pd.concat([name_df,age_df],axis=1)

**#Make a copy of the dataframe**  
copy_df = name_df  

**#Editing the data in name_df**  
name_df.loc[name_df["name"]=="Brad", ["age"]] = 35

**#Change appears in copy_df**  
print(copy_df)

Is this supposed to happen?

`copy_df = name_df ` is **NOT** creating a copy. Its just a reference to the SAME object. — balderman, Oct 03 '21 at 08:44

score 2 · Accepted Answer · answered Oct 03 '21 at 08:46

2

Make a copy. (copy.deepcopy())

import pandas as pd
import copy 
list_name = ["Al","Brad"]  
list_age = [20,30]

name_df = pd.DataFrame(list_name,columns=["name"])  
age_df = pd.DataFrame(list_age,columns=["age"])

name_df = pd.concat([name_df,age_df],axis=1)

copy_df = copy.deepcopy(name_df)  

name_df.loc[name_df["name"]=="Brad", ["age"]] = 35

print(copy_df)

answered Oct 03 '21 at 08:46

balderman

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a=10 b=a a=9 print(b) Alright, thanks. It's different for a variable. – jgoh Oct 03 '21 at 08:50

Setting value to a dataframe using df.loc updates a copy of the dataframe

1 Answers1