pandas merge python
import pandas as pd
df1 = pd.DataFrame({'lkey': ['foo', 'bar', 'baz', 'foo'],
'value': [1, 2, 3, 5]})
df2 = pd.DataFrame({'rkey': ['foo', 'bar', 'baz', 'foo'],
'value': [5, 6, 7, 8]})
df1.merge(df2, left_on='lkey', right_on='rkey')merge dataframe pandas
>>> df1.merge(df2, left_on='lkey', right_on='rkey')
lkey value_x rkey value_y
0 foo 1 foo 5
1 foo 1 foo 8
2 foo 5 foo 5
3 foo 5 foo 8
4 bar 2 bar 6
5 baz 3 baz 7merge pandas
select * from bricks, colours;merge pandas
select * from bricks;
select * from colours;merge pandas
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;pandas merge dataframes
import pandas as pd
pd.merge(restaurant_ids_dataframe, restaurant_review_frame, on='business_id', how='outer')Copyright © 2021 Codeinu
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