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I need to compare two df1 (blue) and df2 (orange), store only the rows of df2 (orange) that are not in df1 in a separate data frame, and then add that to df1 while assigning function 6 and sector 20 for the employees that were not present in df1 (blue)

example

I know how to find the differences between the data frames and store that in a third data frame, but I'm stuck trying to figure out how to store only the rows of df2 that are not in df1.

tailsrockc
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2 Answers2

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This has been answered in pandas get rows which are NOT in other dataframe

Store it as a merge and simply select the rows that do not share common values. ~ negates the expression, select all that are NOT IN instead of IN.

common = df1.merge(df2,on=['ID','Name'])
df = df2[(~df2['ID'].isin(common['ID']))&(~df2['Name'].isin(common['Name']))]

This was tested using some of your data:

df1 = pd.DataFrame({'ID':[125,134,156],'Name':['John','Mary','Bill'],'func':[1,2,2]})
df2 = pd.DataFrame({'ID':[125,139,133],'Name':['John','Joana','Linda']})

Output is:

    ID   Name
1  139  Joana
2  133  Linda
thmasXX
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Can try this:

  1. Get a list with the data os orange u want to keep
  2. Filter df2 with that list
  3. Append

df1 --> blue, df2 --> orange

import pandas as pd

df2['Function'] = 6
df2['Sector'] = 20

ids_df2_keep = [e for e in df2['ID'] if e not in list(df1['ID'])]
df2 = df2[df2['ID'].isin(ids_df2_keep)
df1 = df1.append(df2)
Gabino Antuña Ortiz
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