How to JOIN and MERGE Pandas DataFrame?

Pandas dataframe can be joined or merged provided the column names are identical and the type of both Pandas DataFrame must be compatible. The merge function takes two pandas dataframes as arguments and returns a pandas dataframe with all rows from both dataframes and columns having an identical name to remove duplicates.

merge on index pandas

By Happy HippopotamusHappy Hippopotamus on Jan 10, 2021
pd.merge(df1, df2, left_index=True, right_index=True)

Source: stackoverflow.com

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1

pd merge on multiple columns

By HamboHambo on Mar 26, 2020
new_df = pd.merge(A_df, B_df,  how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])

Source: stackoverflow.com

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7

pandas left join

By Comfortable CockroachComfortable Cockroach on Nov 26, 2020
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")

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6

merge pandas

By Hilarious HareHilarious Hare on Mar 21, 2021
create table bricks (
  brick_id integer,
  colour   varchar2(10)
);

create table colours (
  colour_name           varchar2(10),
  minimum_bricks_needed integer
);

insert into colours values ( 'blue', 2 );
insert into colours values ( 'green', 3 );
insert into colours values ( 'red', 2 );
insert into colours values ( 'orange', 1);
insert into colours values ( 'yellow', 1 );
insert into colours values ( 'purple', 1 );

insert into bricks values ( 1, 'blue' );
insert into bricks values ( 2, 'blue' );
insert into bricks values ( 3, 'blue' );
insert into bricks values ( 4, 'green' );
insert into bricks values ( 5, 'green' );
insert into bricks values ( 6, 'red' );
insert into bricks values ( 7, 'red' );
insert into bricks values ( 8, 'red' );
insert into bricks values ( 9, null );

commit;

Source: livesql.oracle.com

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0

merge pandas

By Hilarious HareHilarious Hare on Mar 21, 2021
select * from bricks, colours;

Source: livesql.oracle.com

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0

merge pandas

By Hilarious HareHilarious Hare on Mar 21, 2021
select * from bricks;

select * from colours;

Source: livesql.oracle.com

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0

Pandas DataFrame is a flexible data frame that can store many different types of data from different sources, and you can also join to other datasets easily.

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