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Remove duplicates with pandas
import pandas as pd
df = df. drop_duplicates( )
df = df. drop_duplicates( subset = "column" )
df = df. drop_duplicates( subset = [ "column" , "column2" ] )
print ( df)
remove duplicate row in df
df = df. drop_duplicates( )
dataframe delete duplicate rows with same column value
df = df. drop_duplicates( subset= [ 'Column1' , 'Column2' ] , keep= 'first' )
import pandas as pd
df = pd. DataFrame( { "A" : [ "foo" , "foo" , "foo" , "bar" ] , "B" : [ 0 , 1 , 1 , 1 ] , "C" : [ "A" , "A" , "B" , "A" ] } )
df. drop_duplicates( subset= [ 'A' , 'C' ] , keep= False )
pandas drop duplicates from column
data = data. drop_duplicates( subset= [ 'City' ] , keep= 'first' )
dataframe delete duplicate rows with same column value
df = df. drop_duplicates( subset= [ 'Column1' , 'Column2' ] , keep= 'first' )
import pandas as pd
df = pd. DataFrame( { "A" : [ "foo" , "foo" , "foo" , "bar" ] , "B" : [ 0 , 1 , 1 , 1 ] , "C" : [ "A" , "A" , "B" , "A" ] } )
df. drop_duplicates( subset= [ 'A' , 'C' ] , keep= False )
remove duplicate columns python dataframe
df = df. loc[ : , ~ df. columns. duplicated( ) ]
remove duplicates in dataframe by index python
df = df[ df. index. duplicated( keep= 'first' ) ]
import pandas as pd
df = df. drop_duplicates( )
df = df. drop_duplicates( subset = "column" )
df = df. drop_duplicates( subset = [ "column" , "column2" ] )
pd df drop duplicates
df. drop_duplicates( subset= [ 'brand' , 'style' ] , keep= 'last' )
how to drop duplicate columns in pandas that dont have the same name?
df2 = df. T. drop_duplicates( ) . T
print ( df2)
df index drop duplicates
df3 = df3[ ~ df3. index. duplicated( keep= 'first' ) ]
drop duplicates data frame pandas python
df. drop_duplicates( keep= False , inplace= True )
drop duplicates columns pandas
df. loc[ : , ~ df. columns. duplicated( ) ]
pandas remove duplicates columns
df = df. loc[ : , ~ df. columns. duplicated( ) ] . copy( )
pandas remove duplicates
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