根据其他列的值分配新值

Question

So I have a dataframe Fruit that have structure look like this

Fruit Sales
Apple 1000
Pear  2000
Peach  400
Banana 200
...

I want to create a new column 'Tag' that assigns value 'Others' to the fruit with sales below rank 10 (sort by sales in descending order), for fruit above(including) rank 10, assign their fruit name to the 'Tag'. So it should look like this assuming Peach and Banana are below sales rank 10.

Fruit Sales  Tag
Apple 1000   Apple
Pear  2000   Pear
Peach  400   Others
Banana 200   Others
...

First, I sort the Fruit dataframe first by sales volume and take the first 10 records:

Top_fruit = Fruit.sort_values(by='Sales',ascending = False)[:10]

Second, I create a Fruit_test dataframe with 'Tag' field added to process the loc function to find the Fruit that's not in the top 10 rank list (ie, Top_fruit) and assign 'Others' to the Tag field.

Fruit_test = Fruit.copy()
Fruit_test['Tag'] =Fruit['Fruit']
Fruit_test.loc[~Fruit_test['Fruit'].isin((Top_fruit)),'Tag'] = 'Others'

However, I keep getting Keyerror: Fruit. Did I do something wrong?

Answer 1

You can do it with just one line of code:

df['Tag'] = df.apply(lambda row: row['Fruit'] if row['Sales'] > 10 else 'Other', axis=1)

Test it:

import pandas as pd


df = pd.DataFrame(
    [['Apple', 1000], ['Pear', 2000], ['Peach', 8], ['Banana', 5]],
    columns=['Fruit', 'Sales'])

print(df, '\n\n------------\n')

df['Tag'] = df.apply(
    lambda row: row['Fruit'] if row['Sales'] > 10 else 'Other', axis=1)

print(df)

Ouput:

    Fruit  Sales
0   Apple   1000
1    Pear   2000
2   Peach      8
3  Banana      5 

------------

    Fruit  Sales    Tag
0   Apple   1000  Apple
1    Pear   2000   Pear
2   Peach      8  Other
3  Banana      5  Other