Work With A Row In A Pandas Dataframe Without Incurring Chain Indexing (not Coping Just Indexing)

My data is organized in a dataframe: import pandas as pd import numpy as np data = {'Col1' : [4,5,6,7], 'Col2' : [10,20,30,40], 'Col3' : [100,50,-30,-50], 'Col4' : ['AAA', 'BBB',

Solution 1:

This should work:

row_of_interest = df.loc['R2', :]
row_of_interest.is_copy = False
row_of_interest['Col2'] = row_of_interest['Col2'] + 1000

Setting .is_copy = False is the trick

Edit 2:

import pandas as pd
import numpy as np

data = {'Col1' : [4,5,6,7], 'Col2' : [10,20,30,40], 'Col3' : [100,50,-30,-50], 'Col4' : ['AAA', 'BBB', 'AAA', 'CCC']}

df = pd.DataFrame(data=data, index = ['R1','R2','R3','R4'])

row_of_interest         = df.loc['R2']
row_of_interest.is_copy = False
new_cell_value          = row_of_interest['Col2'] + 1000
row_of_interest['Col2'] = new_cell_value

print row_of_interest 

df.loc['R2'] = row_of_interest 

print df

df:

    Col1  Col2  Col3 Col4
R1     4    10   100  AAA
R2     5  1020    50  BBB
R3     6    30   -30  AAA
R4     7    40   -50  CCC

Solution 2:

You can remove the warning by creating a series with the slice you want to work on:

from pandas import Series
row_of_interest = Series(data=df.loc['R2', :])
row_of_interest.loc['Col2'] += 1000print(row_of_interest)

Results in:

Col15Col21020Col350Col4BBBName:R2,dtype:object

Solution 3:

most straight forward way to do this

df.loc['R2', 'Col2'] += 1000
df