I have two data frames.
import pandas
import numpy as np
data = {'Name': ['Tom', 'Joseph', 'Krish', 'John','rack','rox','selena','jha'], 'Age': [20, 21,np.nan , 18,20,30,np.nan,np.nan]}
df = pd.DataFrame(data)
print(df)
# Output :
# Name Age
# 0 Tom 20.0
# 1 Joseph 21.0
# 2 Krish NaN
# 3 John 18.0
# 4 rack 20.0
# 5 rox 30.0
# 6 selena NaN
# 7 jha NaN
data = {'Named': ['Raj', 'kir', 'cena','ang'], 'Age': [20, 21,18,30]}
df1 = pd.DataFrame(data)
print(df1)
# Output :
# Named Age
# 0 Raj 20
# 1 kir 21
# 2 cena 18
# 3 ang 30
The df1 is a source data. Now, if the value of age column of df1 matches the column age in df then it has to append the name next to the age column of the df and for suppose if the value in age column of df is null then it shouldn't add anything. It should also be null. It should basically add the name based on the match. As far as I know we can use merge but when I am trying to merge its creating extra rows which is not excepted and the output is also not correct.
Given output and code:
dfinal = df.merge(df, left_on="Age",right_on='Age', how = 'outer')
# My output :
# Name_x Age Name_y
# 0 Tom 20.0 Tom
# 1 Tom 20.0 rack
# 2 rack 20.0 Tom
# 3 rack 20.0 rack
# 4 Joseph 21.0 Joseph
# 5 Krish NaN Krish
# 6 Krish NaN selena
# 7 Krish NaN jha
# 8 selena NaN Krish
# 9 selena NaN selena
# 10 selena NaN jha
# 11 jha NaN Krish
# 12 jha NaN selena
# 13 jha NaN jha
# 14 John 18.0 John
# 15 rox 30.0 rox
# My Excepted Output:
# Name Age Named
# 0 Tom 20.0 Raj
# 1 Joseph 21.0 kir
# 2 Krish NaN NaN
# 3 John 18.0 cena
# 4 rack 20.0 Raj
# 5 rox 30.0 ang
# 6 selena NaN NaN
# 7 jha NaN NaN
