Pandas multiconditional drop using two dataframes

Question

How can I drop some values from a dataframe using another dataframe as parameter?

df1
code | reply
A1   | yes
A2   | yes
A3   | no

df2
code |
A1   |
A1   |
A3   |

df_new = df1.drop(df1['code'] == df2['code'] & df1['reply'] != 'yes')

df_new
code | reply
A1   | yes

Is there a simple way to do this using .drop()?

There are several ways, have a look at those answers: stackoverflow.com/questions/33282119/… — tomasborrella
– tomasborrella, Commented Jan 10, 2023 at 14:25

mozway · Accepted Answer · 2023-01-10 14:27:48Z

2

Use boolean indexing:

out = df1[df1['code'].isin(df2['code']) & df1['reply'].eq('yes')]

Output:

  code reply
0   A1   yes

answered Jan 10, 2023 at 14:27

mozway

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4 Comments

null92 Over a year ago

Is there a "inverse" of .eq() in pandas? I'll use it too

Corralien Over a year ago

ne() is the opposite of eq()

Corralien Over a year ago

@null92. For your information AND and & are not the same thing.

Corralien Over a year ago

@mozway. In fact, I will removed my answer. It does not make sense to use merge here

Corralien · Accepted Answer · 2023-01-10 14:40:26Z

1

The logic is unclear but you can accomplish what you want without the use of drop:

>>> df1[df1['reply'] == 'yes'].merge(df2.drop_duplicates('code'))

  code reply
0   A1   yes

edited Jan 10, 2023 at 14:40

answered Jan 10, 2023 at 14:27

Corralien

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4 Comments

mozway Over a year ago

actually your drop and my indexing are equivalent using De Morgan's law, so yes I always try to keep the most simple variant in such cases ;)

Corralien Over a year ago

That's why I'm pointing it out to the OP.

mozway Over a year ago

I was about to add this variant and the wikipedia link in my answer so I commented instead as you had just edited ;)

Corralien Over a year ago

OK. I removed this part from my answer.

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