Indexing by Position

def tweak_siena_pres(df):
    def int64_to_uint8(df_):
        cols = df_.select_dtypes('int64')
        return (df_
                .astype({col:'uint8' for col in cols}))
    return (df
     .rename(columns={'Seq.':'Seq'})    # 1
     .rename(columns={k:v.replace(' ', '_') for k,v in
        {'Bg': 'Background',
         'PL': 'Party leadership', 'CAb': 'Communication ability',
         'RC': 'Relations with Congress', 'CAp': 'Court appointments',
         'HE': 'Handling of economy', 'L': 'Luck',
         'AC': 'Ability to compromise', 'WR': 'Willing to take risks',
         'EAp': 'Executive appointments', 'OA': 'Overall ability',
         'Im': 'Imagination', 'DA': 'Domestic accomplishments',
         'Int': 'Integrity', 'EAb': 'Executive ability',
         'FPA': 'Foreign policy accomplishments',
         'LA': 'Leadership ability',
         'IQ': 'Intelligence', 'AM': 'Avoid crucial mistakes',
         'EV': "Experts' view", 'O': 'Overall'}.items()})
     .astype({'Party':'category'})  # 2
     .pipe(int64_to_uint8)  # 3
     .assign(Average_rank=lambda df_:(df_.select_dtypes('uint8') # 4
                 .sum(axis=1).rank(method='dense').astype('uint8')),
             Quartile=lambda df_:pd.qcut(df_.Average_rank, 4,
                 labels='1st 2nd 3rd 4th'.split())
            )
    )
import pandas as pd
url = 'https://github.com/mattharrison/datasets/raw/master/data/'\
    'siena2018-pres.csv'
df = pd.read_csv(url, index_col=0)
pres = tweak_siena_pres(df)
print(pres.iloc[1])