Changing a column value in pandas if value in other column matches string

Question

So, I’m a beginner to Pandas and I’m having a little trouble getting something to work.

My task is that I was given a dataframe as follows:

AnimalID	Pet Name	Pet Type
1	Whiskers	Cat
2	Charlie	Dog
3	Spot	Dog
4	Honey	Cat

What I’m attempting to do is add a ‘+’ symbol to the end of the ID if the pet type is a dog.

My solution was to iterate through each row using iterrows() and check if the Pet Type Matches, and if it does, change the ID in that row. My code is below:

import pandas as pd
#df = pd.read_excel('AnimalList.xlsx')
df = pd.DataFrame({'AnimalID':[1,2,3,4], 'Pet Name':['Whiskers', 'Charlie', 'Spot', 'Honey'], 'Pet Type':['Cat', 'Dog', 'Dog', 'Cat']})
for row in df.iterrows():
    if row['Pet Type'].eq('Dog').any():
        row['AnimalID'] = df['AnimalID'].astype(str) + '+'

df

The dataframe is printing without error, but is there any reason that nothing is changing? I have to be missing something obvious. Thank you.

Asked By: dtg108

||

Source

Answer 1

You can apply Series.where to column AnimalID. Its values will be replaced where the condition is False, so we will need to check Series.ne to add + for each row where this column equals Dog.

df['AnimalID'] = df['AnimalID'].where(df['Pet Type'].ne('Dog'), 
                                      df['AnimalID'].astype(str) + '+')

print(df)

  AnimalID  Pet Name Pet Type
0        1  Whiskers      Cat
1       2+   Charlie      Dog
2       3+      Spot      Dog
3        4     Honey      Cat

Answered By: ouroboros1

Answer 2

here is one way to do it using mask

# when condition is true, add + to the ID
df['AnimalID']=(df['AnimalID'].mask(df['Pet Type'].eq('Dog'), 
                                    df['AnimalID'].astype(str) + ('+')))
df

    AnimalID    Pet Name    Pet Type
0          1    Whiskers    Cat
1         2+    Charlie     Dog
2         3+    Spot        Dog
3          4    Honey       Cat

Answered By: Naveed

Changing a column value in pandas if value in other column matches string

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