Suffixes ignored on second merge

[MatzeB]

I am trying to merge multiple dataframe with consecutive merge operations, I want to add a suffix to the name of the newly merged column names. A simplified version of my code looks like this:

from pandas import *
f0 = DataFrame(columns=['data'], data=[1,2,3], index=['a','b','c'])
f1 = DataFrame(columns=['data'], data=[4,5,6], index=['c','b','a'])
f2 = DataFrame(columns=['data'], data=[7,8,9], index=['a','c','b'])
merged = f0
merged = merged.merge(f1, left_index=True, right_index=True, suffixes=("_0", "_1"))
merged = merged.merge(f2, left_index=True, right_index=True, suffixes=("", "_2"))
print merged.columns

With pandas 0.15.2 on python 2.7 this returns:

Index([u'data_0', u'data_1', u'data'], dtype='object')

while I would have expected

Index([u'data_0', u'data_1', u'data_2'], dtype='object')

[jreback]

seems you just want this?

In [45]: pd.concat([f0,f1,f2],axis=1,ignore_index=True)
Out[45]: 
   0  1  2
a  1  6  7
b  2  5  9
c  3  4  8

suffixes only apply if there are duplicate columns which after the first merge there are not (when compared to the 3rd)

In [46]: merged1 = merged.merge(f1, left_index=True, right_index=True, suffixes=("_0", "_1"))

In [47]: merged1
Out[47]: 
   data_0  data_1
c       3       4
b       2       5
a       1       6

In [48]: merged1.merge(f2, left_index=True, right_index=True, suffixes=("", "_2"))
Out[48]: 
   data_0  data_1  data
a       1       6     7
c       3       4     8
b       2       5     9

[MatzeB]

Ah thanks for the explanation, I missed the fact that suffixes only get applied to duplicate column names. And indeed the concat solution is simpler. And for the record: concat(... ignore_index=True) is exactly the opposite of what I want, but with concat(... ignore_index=False) it works nicely.

[jreback]

gr8

keep in mind that you generally don't want to have duplicate columns

you might want a multi level result - use the keys argument to concat