def concat_cols(df1,df2,idx_col,df1_cols,df2_cols,
                df1_suffix,df2_suffix,wc_cols=[],suffix_all=False):
    df1=df1.set_index(idx_col)
    df2=df2.set_index(idx_col)    
    if not len(wc_cols)==0:
        for wc in wc_cols:
            df1_cols=df1_cols+[c for c in df1.columns if wc in c]
            df2_cols=df2_cols+[c for c in df2.columns if wc in c]
    combo=pd.concat([df1.loc[:,df1_cols],df2.loc[:,df2_cols]],axis=1)
    if suffix_all:
        df1_cols=["%s%s" % (c,df1_suffix) for c in df1_cols]
        df2_cols=["%s%s" % (c,df2_suffix) for c in df2_cols]
    else:
        common_cols=[col for col in df1_cols if col in df2_cols]
        for col in common_cols:
            df1_cols[df1_cols.index(col)]="%s%s" % (col,df1_suffix)
            df2_cols[df2_cols.index(col)]="%s%s" % (col,df2_suffix)
    combo.columns=df1_cols+df2_cols
    combo.index.name=idx_col
    return combo