如何高效实现支持各单元格自定义输入的Pandas DataFrame日历

现有资产列表assets = ['1', '2', '3', ..., 'n']，每个资产在指定日期范围date_range = ['2023-01-01', '2023-01-02', ..., '202x-xx-xx']内的每个日期都对应唯一输入。目前已有实现代码，但逻辑既不合理也不高效，希望大家提供优化思路或解决方案。我已经开始尝试用pd.date_range寻找替代方案。

当前实现代码 #

# list of assets
assets = ['A1','A2','A3','A4']

# Dataframe with data that will be used to build the calendar and be the reference for inputs
data = {'PRODUCT': ['A1', 'B1', 'C1', 'D1'], 'DATE': [2023-01-02, 2023-07-15, 2023-12-21]}   
df_data = pd.DataFrame(data)
  
# Building the columns of the calendar
today = pd.Timestamp(2023, 1, 1)
today_str = str(today)

columns = list()
columns.append('ASSETS')

date_max = df_data['DATE'].max()
delta = (date_max - today).days  # 注：原代码此处误写为data_max，应为date_max

for i in range(0, delta+1):
    columns.append(str((today+timedelta(days=i)).date()))

# Building the calendar and using the assets as index
df_calendar = pd.DataFrame(columns = columns)
df_calendar['ASSETS'] = assets
df_calendar.index = list(df_calendar['ASSETS'])
df_calendar= df_calendar.drop('ASSETS', axis=1)
df_calendar= df_calendar.fillna(0)

当前生成结果 #

内容的提问来源于stack exchange，提问作者Douglas Mateus Machado