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'])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'])python inner join based on two columns
df = pd.merge(left=df1, right=df2, on=['var_1', 'var_2'], how='inner']pandas merge two columns from different dataframes
#suppose you have two dataframes df1 and df2, and
#you need to merge them along the column id
df_merge_col = pd.merge(df1, df2, on='id')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 add multiple columns to pandas dataframe
# Basic syntax:
df[['new_column_1_name', 'new_column_2_name']] = pd.DataFrame([[np.nan, 'word']], index=df.index)
# Where the columns you're adding have to be pandas dataframes
# Example usage:
# Define example dataframe:
import pandas as pd
import numpy as np
df = pd.DataFrame({
'col_1': [0, 1, 2, 3],
'col_2': [4, 5, 6, 7]
})
print(df)
col_1 col_2
0 0 4
1 1 5
2 2 6
3 3 7
# Add several columns simultaneously:
df[['new_col_1', 'new_col_2', 'new_col_3']] = pd.DataFrame([[np.nan, 42, 'wow']], index=df.index)
print(df)
col_1 col_2 new_col_1 new_col_2 new_col_3
0 0 4 NaN 42 wow
1 1 5 NaN 42 wow
2 2 6 NaN 42 wow
3 3 7 NaN 42 wow
# Note, this isn't much more efficient than simply doing three
# separate assignments, e.g.:
df['new_col_1'] = np.nan
df['new_col_2'] = 42
df['new_col_3'] = 'wow'merge two columns pandas
df["period"] = df["Year"] + df["quarter"]Copyright © 2021 Codeinu
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