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I have a several dataframes with the same name. Each dataframe has one row and two columns. One column is common in all of dataframes. I would like to left-join them together. Assuming the name of dataframes is same. I have no plan on differing their names from each other as they are so many of them and I am just putting a few of them here. Is there any way that i can do left join them and generate the desired output mentioned below?

Here is the dataframes:

 col1 col2_4
0 1 2

 col1 col2_9
0 1 10

 col1 col2_1
0 1 12

 col1 col2_3
0 1 5

Output:

 col1 col2_4 col2_9 col2_1 col_3
0 1 2 10 12 5

Code:

group = df.groupby([randomcolumnname])
for name, groups in group:
 #do some stuff for groups
 print(groups)
 #I want to join the groups dataframes after this line(some groups dataframes are given above)

Thanks in advance!

I believe you need for left join merge with list of DataFrames by column col1:

dfs = [df1, df2, df3, df4]

from functools import reduce

df = df_final = reduce(lambda left,right: pd.merge(left,right,on='col1', how='left'), dfs)
print (df)
 col1 col2_1 col2_2 col2_3 col2_4
0 1 2 10 12 5

Or for outer join create index by set_index and concat:

df = pd.concat([x.set_index('col1') for x in dfs], axis=1).reset_index()
print (df)
 col1 col2_1 col2_2 col2_3 col2_4
0 1 2 10 12 5

EDIT:

I think better is use custom function with GroupBy.apply:

def func(x):
 print (x)
 #do some stuff for groups

 return x


group = df.groupby([randomcolumnname]).apply(func)

If not possible, for lsit of DataFrames use:

dfs = 
group = df.groupby([randomcolumnname])
for name, groups in group:
 #do some stuff for groups

 print(groups)
 dfs.append(groups)