How to Create Conditional Columns in Pandas | IF ELSE Condition in Pandas Data Frame

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In this video we will learn how to create new columns in pandas based on the value of other columns.
data:
order_id,product_name,category,city,sales,profit
CA-2020-152156,p1,Furniture,Bangalore,10000,500
CA-2020-138688,p2,Furniture,Bangalore,20000,400
US-2019-108966,p3,Technology,Chennai,25000,200
CA-2021-114412,p4,Office Supplies,Chennai,30000,250
CA-2020-161389,p5,Technology,Mysore,35000,800
US-2019-118983,p6,Office Supplies,Mysore,40000,700
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#python #pandas #dataanalytics

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2 окт 2024

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Комментарии : 36

@sashikanthpalleti5757 Год назад

The operation is happening row by row. I was asked in an interview with ServiceNow how to add a new column in pandas dataframe with existing column string length without using row by row operations. Ex: Sno name 1 abch 2 sujit 3 pqr Output: Sno name length 1 abch 4 2 sujit 5 3 pqr 3

@ankitbansal6 Год назад

That you can simply create using df['len']= df.name.str.len()

@sashikanthpalleti5757 Год назад

@@ankitbansal6 I said i will use the apply() method and they were not convinced. What is the difference in apply() method and directly using Len() ?

@ankitbansal6 Год назад

@@sashikanthpalleti5757 apply function is a loop itself. Direct assignment is a dataframe operation and faster.

@Mayank-jw9yy 5 месяцев назад

Great video Ankit

@parveen8122 Год назад

Solution using apply function ========================= using apply function , I think it wii be much more efficient and increases readibility. in your case i think the same df will run twice , 1st for KN and then for TN def match(city): if city=="Bangalore" or city=='Mysore': return 'Karnataka' else: return 'TN' df["State"] = df["city"].apply(match)

@ankitbansal6 Год назад

Apply runs a loop

@sudiipkumarbasu4194 Год назад

Great experience

@bodybuildingmotivation5438 Месяц назад

make more scenerios base qut on python

@mihirsamant9352 Год назад

I dont know why Ankit is soo underrated on RU-vid. He got skills to make difficult topic super easy. Thanks for doing this but you are tooo good with skills and knowledge #Respect !

@ankitbansal6 Год назад

Thank you 😊

@khushishrivastava331 Год назад

Please create a video for scenarios where Lambda function can be used.

@ankitbansal6 Год назад

@ektakumari4496 Год назад

👌grt content

@ankitbansal6 Год назад

Thank you 😊

@arunshaw1285 Год назад

Solution using numpy's # np.select(conditions, values) import numpy as np conditions = [(df['profit']250) & (df['profit']500)] values=['low','medium','high'] df['profit_category'] = np.select(conditions,values) df