CODEWITHSUNDEEP
pythonpandasdataframedata-science
nrmb
nrmb

Reputation: 490

Drop a row and column at the same time Pandas Dataframe

I have a dataframe which is something like this

Victim Sex       Female    Male  Unknown
Perpetrator Sex                         
Female            10850   37618       24
Male              99354  299781       92
Unknown           33068  156545      148

I'm planning to drop both the row indexed as 'Unknown' and the column named 'Unknown'. I know how to drop a row and a column but I was wondering whether you could drop a row and a column at the same time in pandas? If yes, how could it be done?

Upvotes: 3

Views: 4296

Answers (3)

sargupta
sargupta

Reputation: 1043

You can delete columns and rows at the same time in one line just with their position. For example, if you want delete column 2,3 and 5 and at the same time if you want to remove index 0,1 and 3 along with the last row of the dataframe, you can do this by following,

df.drop(df.columns[[2,3,5]], axis = 1).drop(df.index[[0,1,3,-1]])

Upvotes: 3

jezrael
jezrael

Reputation: 863196

I think closest 'at the same time' is select by loc and difference:

print (df.index.difference(['Unknown']))
Index(['Female', 'Male'], dtype='object')

print (df.columns.difference(['Unknown']))
Index(['Female', 'Male'], dtype='object')

df = df.loc[df.index.difference(['Unknown']), df.columns.difference(['Unknown'])]
print (df)
Victim Sex       Female    Male
Perpetrator Sex                
Female            10850   37618
Male              99354  299781

Upvotes: 5

Quickbeam2k1
Quickbeam2k1

Reputation: 5437

This should do the job, however it's not really at the same time, but no intermediate object is returned to you.

df.drop("Unknown", axis=1).drop("Unknown", axis=0)

So for a concrete Example:

df = pd.DataFrame([[1,2],[3,4]], columns=['A', 'B'], index=['C','D'])
print(df)
   A  B
C  1  2
D  3  4

the call

df.drop('B', axis=1).drop('C', axis=0)

returns

   A
D  3

Upvotes: 6

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