merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outermerge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outerjoin 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')pandas merge multiple dataframes
import pandas as pd
from functools import reduce
# compile the list of dataframes you want to merge
data_frames = [df1, df2, df3]
df_merged = reduce(lambda left,right: pd.merge(left,right,on=['key_col'],
how='outer'), data_frames)combine two dataframe in pandas
# Stack the DataFrames on top of each other
vertical_stack = pd.concat([survey_sub, survey_sub_last10], axis=0)
# Place the DataFrames side by side
horizontal_stack = pd.concat([survey_sub, survey_sub_last10], axis=1)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_colCopyright © 2021 Codeinu
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