Я предполагал, что вывод будет другим DataFrame.
import pandas as pd
import numpy as np
from nltk import flatten
import copy
df = pd.DataFrame({'EventName': ['sydney', 'sydney', 'sydney', 'sydney', 'sydney', 'sydney'],
'Date': ['2019-01.01', '2019-01.01', '2019-01.01', '2019-01.01', '2019-01.01', '2019-01.01'],
'Race_Number': ['Race1', 'Race1', 'Race1', 'Race2', 'Race2', 'Race3'],
'Number': [4, 7, 2, 9, 5, 10]
})
print(df)
dic={}
for rows in df.itertuples():
if rows.Race_Number in dic:
dic[rows.Race_Number] = flatten([dic[rows.Race_Number], rows.Number])
else:
dic[rows.Race_Number] = rows.Number
copy_dic = copy.deepcopy(dic)
seq = np.arange(0,len(dic.keys()))
for key, n_key in zip(copy_dic, seq):
dic[n_key] = dic.pop(key)
df = pd.DataFrame([dic])
print(df)