How to perform a loop on a dataframe, removing rows conditionally and restarting the loop on a recalculated dataframe with each removal?

Hello,

I am processing some data and I need my algorithm to perform the comparison between two lines and remove the one that is worse, according to some conditions.

Each time the algorithm performs the removal, it must recalculate the dataframe, since one of the conditions depends on the relationship of the bottom line to the top.

My dataframe has the following format

df = n° de fios 1     diametro 1     n° de fios 2     diametro 2     seção total   relação
           n11             d11             n21             d21           st1       st2/st1
           n12             d12             n22             d22           st2       st3/st2

This continues for several lines.

O what my algorithm does is:

• reads the dataframe of an excel, which has the first 5 columns
• calculates the last column
• adds another column with a rank based on the first column (coming from a dict)
• scroll through the rows, through a loop for n in range(0, len(df)-1)
• if the relation is less than 1.03, you must remove one of the two rows
• There is a set of conditions that must be met for the row n+1 to be removed, otherwise removes the line n (conditions include the rank).
• when a row is removed, reset the index, remove the column rank, add the dataframe to a excel, and apply the loop to the new excel.

My code is as follows:

class Rank_and_drop(object):
    def __init__(self): # define os dicts
    #exemplo
    self.dict_mc_112_2p_cu = {'0.71': 0, '0.75': 1, '0.67': 2, '0.8': 3, '0.85': 4, '0.63': 5, '0.45': 6, '0.475': 7, '0.5': 8, '0.53': 9, '0.56': 10, '0.6': 11}
def recalc_df(self, file, sheet):
    # lê a tabela
    df_final = pd.read_excel(file, sheet_name=sheet)
    # converte os numeros para strings para poder usar o self.dict
    df_final = df_final.astype(str)

    df_final = df_final.drop(columns=['rsc'])
    df_final = df_final.sort_values(by='sc')
    df_final = df_final.reset_index(drop=True)

    aux = df_final.loc[:, 'sc']
    aux = aux.reset_index(drop=True)

    aux2 = aux.drop(0)
    aux2 = aux2.reset_index(drop=True)
    aux2 = aux2.append(aux2.tail(1), ignore_index=True)

    for x in range(len(aux)):
        aux[x] = (round(float(aux2[x])/float(aux[x]), 3))

    aux = aux.rename('rsc')

    df_final['rsc'] = aux

    df_final = df_final.astype(str)

    df_final['rnk'] = df_final['d1'].map(dict_)

    return df_final

def loop(self, file, sheet):
    df = self.recalc_df(file, sheet)

    for n in range(0,len(df)-1):
        c_0 = float(df.at[n, 'rsc']) <= 1.03

        c_1 = (df.at[n, 'n2'] == '0') and (df.at[n+1, 'n2'] == '0')
        c_1_1 = df.at[n+1, 'rnk'] >= df.loc[n, 'rnk']
        c_1_2 = float(df.at[n, 'n1']) < float(df.at[n+1, 'n1'])
        c_2 = (df.at[n, 'n2'] == '0') and (df.at[n+1, 'n2'] != '0')
        c_4 = (df.at[n, 'n2'] != '0') and (df.at[n+1, 'n2'] != '0')
        c_4_1 = df.at[n+1, 'rnk'] == df.at[n, 'rnk']
        c_4_1_1 = float(df.at[n+1, 'd2']) < float(df.at[n, 'd2'])
        c_4_2 = df.at[n+1, 'rnk'] > df.at[n, 'rnk']

        if c_0:
            if (((c_1) and ((c_1_1) or (c_1_2))) or (c_2) or ((c_4) and ((((c_4_1) and (c_4_1_1)) or (c_4_2))))):
                df = df.drop(n+1)

            else:
                df = df.drop(n)


            df = df.reset_index(drop=True)
            df = df.drop(columns=['rnk'])
            df.to_excel('{0}.xlsx'.format(sheet), index=False, sheet_name=sheet)
            self.loop('{0}.xlsx'.format(sheet), sheet)

        else:
            pass

        n = n+1

    df.to_excel('{0}.xlsx'.format(sheet), index=False, sheet_name=sheet)
    return df 

Now the problem is that my loop doesn't work the way I expect it to... It starts correctly, and to a certain extent even does the expected, however, from a certain point, the algorithm looks like it gives a bugged , and removes several rows it shouldn't, and in the end returns a KeyError.

Any idea what I can do to accomplish this task, more optimally and without these errors?

Edit: I have several dataframes that I want to do this, of varying sizes, in the smallest of them (35 lines), the code correctly performs the function, however, returns the KeyError. In another dataframe, of 690 rows, the problem of removing several rows occurs.