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

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
Zero to hero(Advance) SQL Aggregation:
• All About SQL Aggregat...
Most Asked Join Based Interview Question:
• Most Asked SQL JOIN ba...
Solving 4 Trick SQL problems:
• Solving 4 Tricky SQL P...
Data Analyst Spotify Case Study:
• Data Analyst Spotify C...
Top 10 SQL interview Questions:
• Top 10 SQL interview Q...
Interview Question based on FULL OUTER JOIN:
• SQL Interview Question...
Playlist to master SQL :
• Complex SQL Questions ...
Rank, Dense_Rank and Row_Number:
• RANK, DENSE_RANK, ROW_...
#python #pandas #dataanalytics

[@mihirsamant9352]

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

[@ankitbansal6]

Thank you 😊

[@Mayank-jw9yy]

Great video Ankit

[@ratneshraj4653]

Please continue the series just like SQL series.
Thanks in advance

[@ssteo4136]

thanks. very useful

[@pratibhamishra869]

Please post regular videos in This playlist. This is great actually!

[@ankitbansal6]

Sure

[@sudiipkumarbasu4194]

Great experience

[@avi8016]

Great video as usual sir💯

[@ankitbansal6]

Thank you 😊

[@hameedkaryab]

Thank you very much for the clear explanation.😊

[@ankitbansal6]

Glad it was helpful!

[@divsp777]

Thank you for this amazing video. kudos

[@ankitbansal6]

Glad you enjoyed it!

[@sashikanthpalleti5757]

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]

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

[@sashikanthpalleti5757]

@@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]

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

[@sonal008]

How to do this for for bigger dataset. Like I have 354 unique product ID and I have to assign
Url to each in new column.

[@ektakumari4496]

👌grt content

[@ankitbansal6]

Thank you 😊

[@rishav144]

great video sir ...need more pandas video

[@ankitbansal6]

Sure

[@user-zf3it3vw2e]

good

[@shravank1147]

amazing ... its helpful..please upload more vids on pandas

[@ankitbansal6]

Sure

[@salmankhan-vq7pc]

@@ankitbansal6 Hi bro, this is the playlist im looking for. Very helpful. Kindly create more content on pandas and numpy. Cheers.

[@khushishrivastava331]

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

[@ankitbansal6]

Ok

[@parveen8122]

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]

Apply runs a loop

[@LONGTRINH-ut4nt]

how i can compare 2 columns using if else in order to classify? Ex: [Column A > Column B: 'Good Customer' else 'Bad Customer']

[@SheikhSirajumMonir]

were you able to find a solution for it?

[@arunshaw1285]

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