PYTHON

merge two dataframes based on column

df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column

df_outer

combine dataframes with two matching columns

merged_df = DF2.merge(DF1, how = 'inner', on = ['date', 'hours'])

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')

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])