How to to make a join in data frame if two columns have empty values

Question

I have two dataframes with 3 columns each

df.A= x:1,4
      y:2,5
      Z: ,6

df.B= x:1,4
      y:2,5
      C: ,6

My output dataframe after joining the above two dataframes

df[C]=A.merge(B,left_on=['X','Y','Z'],right_on=['X','Y','C'],how='left')

I am only getting the 2 row values but not the first row

df[C]=x:4
      y:5
      z:6

How can I deal with these missing values scenarios with joins, let me know if you are not able to understand the question

Answer 1

Updating with blanks:

import pandas as pd
import numpy as np
dfA = pd.DataFrame({"X":[1,4],
                   "Y":[2,5],
                   "Z":['',6]})
print(dfA)

dfB = pd.DataFrame({"X":[1,4],
                   "Y":[2,5],
                   "C":['',6]})

print(dfB)

dfC=dfA.merge(dfB, left_on=['X','Y','Z'], right_on=['X','Y','C'], how='left')

print(dfC)

Outputs:

   X  Y  Z
0  1  2   
1  4  5  6
   X  Y  C
0  1  2   
1  4  5  6
   X  Y  Z  C
0  1  2      
1  4  5  6  6

You might have whitespace issues, where one dataframe has a single space an the other has two or more spaces.

---

I don't quite understand... You code appears to be working as expected. Here is MCVE:

import pandas as pd
import numpy as np
dfA = pd.DataFrame({"X":[1,4],
                   "Y":[2,5],
                   "Z":[np.nan,6]})
print(dfA)

Output:

   X  Y    Z
0  1  2  NaN
1  4  5  6.0

And,

dfB = pd.DataFrame({"X":[1,4],
                   "Y":[2,5],
                   "C":[np.nan,6]})

print(dfB)

Output:

   X  Y    C
0  1  2  NaN
1  4  5  6.0

Merge left yeilds, dfC:

dfC=dfA.merge(dfB, left_on=['X','Y','Z'], right_on=['X','Y','C'], how='left')

print(dfC)

Output:

   X  Y    Z    C
0  1  2  NaN  NaN
1  4  5  6.0  6.0

Were you expecting something different?