merge columns pandas code example

Example 1: 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')

Example 2: how to merge two dataframes

df_merge_col = pd.merge(df_row, df3, on='id')

df_merge_col

Example 3: 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

Example 4: merge two columns pandas

df["period"] = df["Year"] + df["quarter"]

Example 5: how to concat on the basis of particular columns in pandas

In [6]: result = pd.concat(frames, keys=['x', 'y', 'z'])

Example 6: 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'