Operation on pandas data frames

Question

I don't know how to describe my problem in words, I just model it

Problem modeling:

Let say we have two dataframes df1, df2 with the same columns

df1

idx | col1 | col2 | col3 |  col4 
---------------------------------
 0  |  1   | -100 |   2  |  -100

df2

idx | col1 | col2 | col3 |  col4
---------------------------------
 0  |  12  |  23  |  34  |   45

Given these two df-s we get

df_result

idx | col1 | col2 | col3 |  col4 
---------------------------------
 0  |  1   |  23  |   2  |   45

I.e. we get df1 where all -100 substituted with values from df2 accordingly.

Question: How can I do it without for-loop? In particular, is there an operation in pandas or on two lists of the same size that could do what we need?

PS: I can do it with for loop but it will be much slower.

If my answer is what you were looking for you can accept it: stackoverflow.com/help/someone-answers — Ale
– Ale, Commented Sep 21, 2020 at 21:44

Ale · Accepted Answer · 2020-04-01 08:00:33Z

2

You can use this:

df1[df1==-100] = df2

This is how it works step-by-step:

import pandas as pd
import numpy as np

df1 = pd.DataFrame(np.array([[1,-100,2,-100],[-100,3,-100,-100]]), columns=['col1','col2','col3','col4'])
df1

col1    col2    col3    col4
1       -100    2       -100
-100    3       -100    -100


df2 = pd.DataFrame(np.array([[12,23,34,45],[1,2,3,4]]), columns=['col1','col2','col3','col4'])
df2

col1    col2    col3    col4
12      23      34      45
1       2       3       4

By using boolean indexing you have that

df1==-100

col1    col2    col3    col4
False   True    False   True
True    False   True    True

So when True you can assign the corresponding value of df2:

df1[df1==-100]=df2
df1

col1    col2    col3    col4
1       23      2       45
1       3       3       4

answered Apr 1, 2020 at 8:00

Ale

1,02914 silver badges31 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Operation on pandas data frames

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related