PYTHON

pandas join two columns

df['FullName'] = df[['First_Name', 'Last_Name']].agg('-'.join, axis=1)

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

df_merge_col

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')

how to merge two pandas dataframes on a column

import pandas as pd
T1 = pd.merge(T1, T2, on=T1.index, how='outer')

merge two columns pandas

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

how to merge two column pandas

DataFrame["new_column"] = DataFrame["column1"] + DataFrame["column2"] 

put two columns together in one column in pandas dataframe

# First dataframe with three columns
dlist=["vx","vy","vz"]
df=pd.DataFrame(columns=dlist)
df["vx"]=df1["v2x"]
df["vy"]=df1["v2y"]
df["vz"]=df1["v2z"]
# second dataframe with three columns
dlist=["vx","vy","vz"]
df0=pd.DataFrame(columns=dlist)
df0["vx"]=df2["v1x"]
df0["vy"]=df2["v1y"]
df0["vz"]=df2["v1z"]
# Here with concat we can create new dataframe with garther both in one
# YOU CAN PUT SOME VALUES IN EACH AND CHECK IT
# WHAT INSIDE THE CONCAT MUST BE A LIST OF DATAFRAME
v = pd.concat([df,df0])