how to preserve original indexes in the new dataframe

Question

def answer_eight():
    templist = list()
    for county, region, p15, p14, ste, cty in zip(census_df.CTYNAME,
                                        census_df.REGION,
                                        census_df.POPESTIMATE2015,
                                        census_df.POPESTIMATE2014,
                                        census_df.STNAME,
                                        census_df.CTYNAME):
        # print(county)
        if region == 1 or region == 2:
            if county.startswith('Washington'):
                if p15 > p14:
                    templist.append((ste, cty))
    labels = ['STNAME', 'CTYNAME']
    df = pd.DataFrame.from_records(templist, columns=labels)
    return df

         STNAME            CTYNAME
0          Iowa  Washington County
1     Minnesota  Washington County
2  Pennsylvania  Washington County
3  Rhode Island  Washington County
4     Wisconsin  Washington County

All these CTYNAME has different indexes in the original census_df. How could I transfer them over to the new DF so the answer looks like:

         STNAME            CTYNAME
12          Iowa  Washington County
222     Minnesota  Washington County
400  Pennsylvania  Washington County
2900  Rhode Island  Washington County
2999     Wisconsin  Washington County

Answer 1

I'd include the index with the other things your are zipping

def answer_eight():
    templist = list()
    index = list()
    zipped = zip(
        census_df.CTYNAME,
        census_df.REGION,
        census_df.POPESTIMATE2015,
        census_df.POPESTIMATE2014,
        census_df.STNAME,
        census_df.CTYNAME,
        census_df.index
    )        
    for county, region, p15, p14, ste, cty, idx in zipped:
        # print(county)
        if region == 1 or region == 2:
            if county.startswith('Washington'):
                if p15 > p14:
                    templist.append((ste, cty))
                    index.append(idx)
    labels = ['STNAME', 'CTYNAME']
    df = pd.DataFrame(templist, index, labels)
    return df.rename_axis(census_df.index.name)