merge on index pandas
pd.merge(df1, df2, left_index=True, right_index=True)
merge on index pandas
pd.merge(df1, df2, left_index=True, right_index=True)
pd merge on multiple columns
new_df = pd.merge(A_df, B_df, how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])
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')
joins in pandas
pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])
merge dataframe
In [46]: result = pd.merge(left, right, how="right", on=["key1", "key2"])
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 7
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