CODEWITHSUNDEEP
pythonpandas
moe_95
moe_95

Reputation: 417

Remove duplicate and original row - Pandas

I am attempting to drop all records which have a duplicate from the below DataFrame df.

  sales_id sales_line
    100      1
    100      1
    200      1
    300      2
    300      2
    400      3
    500      1
    500      1
    600      5

The expected output I am trying to achieve is seen below. 

sales_id sales_line
    200      1
    400      3
    600      5

Any assistance that anyone could provide would be greatly appreciated.

Upvotes: 2

Views: 1370

Answers (3)

coder3521
coder3521

Reputation: 2646

dropping ALL duplicte values

data.drop_duplicates(keep = False, inplace = True)

This would give you the expected output

Upvotes: 1

jezrael
jezrael

Reputation: 863166

Use DataFrame.drop_duplicates with keep=False for remove duplicates in all columns:

df = df.drop_duplicates(keep=False)
print (df)
   sales_id  sales_line
2       200           1
5       400           3
8       600           5

Upvotes: 6

Daemon Painter
Daemon Painter

Reputation: 3490

You can try with drop_duplicates(self, subset=None, keep="first", inplace=False)

In your case, the important bit of the function is the keep=False.

import pandas as pd


data = { 'sales_id' : [100, 100, 200, 300, 300, 400, 500, 500, 600], 'sales_line' : [1, 1, 1, 2, 2, 3, 1, 1, 5] }

df = pd.DataFrame(data)
print('Source DataFrame:\n', df)

df_dropped = df.drop_duplicates(subset=['sales_id', 'sales_line'], keep=False)
print('Result DataFrame:\n', df_dropped)

Upvotes: 1

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