Merging of DataFrames does not keep order of suffixes
The documentation of the merge of dataframes state that with the suffixes parameter you can set the columnname suffixes for the left and right dataframe respectively (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html).

According to my example the suffixes are first sorted alphabetically.

```
A = pd.DataFrame({'prodID':[0,1,2,3,4],'units':[5,6,7,8,9]})
B = pd.DataFrame({'prodID':[0,1,2,3,4],'units':[10,11,12,13,14]})

merged = pd.merge(B,A,on='prodID',suffixes={'_b','_a'})
print(merged)
```
Actual result:
```
   prodID  units_a  units_b
0       0       10        5
1       1       11        6
2       2       12        7
3       3       13        8
4       4       14        9
```
What I expected to get:
```
   prodID  units_b  units_a
0       0       10        5
1       1       11        6
2       2       12        7
3       3       13        8
4       4       14        9
```
When I use the suffixes i want the left dataframe, in my example B, to get the left suffix, '_b'. And the right dataframe the right suffix. A lot of bugs can occur due to the selection of the wrong columns.