pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")pandas left join
df.merge(df2, left_on = "doc_id", right_on = "doc_num", how = "left")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')joins in pandas
pd.merge(product,customer,on='Product_ID')merge two df
bigdata = pd.concat([data1, data2], ignore_index=True, sort=False)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)]python dataframe left join
>>> left.merge(right, on='user_id', how='left')Copyright © 2021 Codeinu
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