I want to add a column in my Data Frame according to some condition

Question

I want to add another column RevisedPrice based on mentioned condition

if Price=1500 then RevisedPrice=Price+(Price*0.15) else if Price=800 then RevisedPrice=Price+(Price*0.10) else RevisedPrice=Price+(Price*0.5)

Below is my code------------

df['RevisedPrice']=[x+(0.15*x) if x==1500 else x+(0.10*x) if x==800 else x+(0.05*x) for x in df['Price']]

i am getting my column value as RevisedPrice=Price+(Price*0.5)

Shubham Sharma · Accepted Answer · 2020-02-29T10:25:15.830

You can use the apply function of pandas dataframe to achieve the desired result. Here is the code you might want to try:

def transform(row):
    if row["Price"] == 1500:
        scale = 0.15
    elif row["Price"] == 800:
        scale = 0.10
    else:
        scale = 0.5

    return row["Price"] + row["Price"] * scale

df["RevisedPrice"] = df.apply(transform, axis=1)

And when you execute >>>print(df.head())

OUTPUT:

         Date   Event  Price  RevisedPrice
0   11/8/2011   Music   1500        1725.0
1   11/9/2011  Poetry    800         880.0
2  11/10/2011   Music   1500        1725.0
3  11/11/2011  Comedy   1200        1800.0
4  11/12/2011  Poetry    800         880.0

You should avoid using ```.apply(...)```: https://stackoverflow.com/a/54432584/11610186 — Grzegorz Skibinski, Feb 29 '20 at 12:44

talatccan · Answer 2 · 2020-02-29T11:13:22.903

1

This is my approach with lambda. You can apply multiple condition with this way.

df['RevisedPrice'] = df['Price'].apply(lambda x: x*1.15 if x == 1500 else (x*1.1 if x == 800 else x*1.05))

Output:

    Event  Price  RevisedPrice
0   music   1500        1725.0
1  poetry    800         880.0
2   music   1500        1725.0
3  comedy   1200        1260.0
4  poetry    800         880.0

PS: I assume RevisedPrice for else condition is x+(x*0.05). If it is x+(x*0.5) you can modify the condition as well.

edited Feb 29 '20 at 11:13

answered Feb 29 '20 at 11:07

talatccan

743
5
19

You should avoid using ```.apply(...)```: https://stackoverflow.com/a/54432584/11610186 – Grzegorz Skibinski Feb 29 '20 at 12:45

Grzegorz Skibinski · Answer 3 · 2020-02-29T10:28:23.397

0

Try:

mapping={1500: 1.15, 800: 1.1}
df['RevisedPrice']=df['Price'].map(mapping).fillna(1.5).mul(df['Price'])

So map all the Price to proper coefficient, fill the else (since .map maps 1:1, you can't put else there). Then just multiply it by the base column - Price

edited Feb 29 '20 at 10:28

answered Feb 29 '20 at 10:17

Grzegorz Skibinski

12,624
2
11
34

I want to add a column in my Data Frame according to some condition

3 Answers3