merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
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)]
merge two dataframes based on column
df_merge_col = pd.merge(df_row, df3, on='id')
df_merge_col
merge two columns pandas
df["period"] = df["Year"] + df["quarter"]
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