Answers for "join on pandas"

7

join on column pandas

# df1 as main df and use the feild from df2 and map it into df1

df1.merge(df2,on='columnName',how='left')
Posted by: Guest on May-15-2020
5

joins in pandas

pd.merge(product,customer,left_on='Product_name',right_on='Purchased_Product')
Posted by: Guest on May-31-2020
1

joins in pandas

pd.merge(product,customer,on='Product_ID')
Posted by: Guest on May-31-2020
3

Joins with another DataFrame

# Joins with another DataFrame

df.join(df2, df.name == df2.name, 'outer').select(
  df.name, df2.height).collect()
# [Row(name=None, height=80), Row(name=u'Bob', height=85), Row(
#   name=u'Alice', height=None)]

df.join(df2, 'name', 'outer').select('name', 'height').collect()
# [Row(name=u'Tom', height=80), Row(name=u'Bob', height=85), Row(
#   name=u'Alice', height=None)]

cond = [df.name == df3.name, df.age == df3.age]
df.join(df3, cond, 'outer').select(df.name, df3.age).collect()
# [Row(name=u'Alice', age=2), Row(name=u'Bob', age=5)]

df.join(df2, 'name').select(df.name, df2.height).collect()
# Row(name=u'Bob', height=85)]

df.join(df4, ['name', 'age']).select(df.name, df.age).collect()
# [Row(name=u'Bob', age=5)]
Posted by: Guest on April-20-2020
4

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
Posted by: Guest on October-11-2020

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