You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
56 lines
2.3 KiB
Python
56 lines
2.3 KiB
Python
import pandas as pd
|
|
|
|
df = pd.read_excel(r'C:\Users\鸽子\Desktop\20231229.xlsx', sheet_name=1)
|
|
df['pt_date'] = pd.to_datetime(df['pt_date'])
|
|
|
|
# 移动平均
|
|
dict_big = {}
|
|
dict_ok = {}
|
|
|
|
for city in df['city_name'].drop_duplicates():
|
|
|
|
df_city1 = df[(df['city_name'] == city) & (df['county_name'].isnull())].set_index('pt_date').loc['2023-12'].sort_index()
|
|
resut_df = pd.DataFrame({})
|
|
index_level = []
|
|
tq_list = []
|
|
pred_list = []
|
|
loss_list = []
|
|
rate_list = []
|
|
|
|
for level in df_city1.columns[2:]:
|
|
|
|
# index_level.append(level)
|
|
df_moving_avg = pd.DataFrame(df_city1[level], index=df_city1.index)
|
|
future = pd.date_range(start='2023-12-28', periods=4, freq='D')
|
|
|
|
for date in future:
|
|
df_moving_avg.loc[date, level] = df_moving_avg[-3:].mean().values
|
|
resut_df = pd.concat([resut_df, df_moving_avg], axis=1)
|
|
print(city[4:6])
|
|
print(resut_df)
|
|
|
|
# loss = (df_city1[level].tail(-3).sum() - df_moving_avg.tail(-3).sum()) / df_city1[level].sum()
|
|
# tq_list.append(df_city1[level].sum())
|
|
# pred_list.append(df_moving_avg[level].sum())
|
|
# loss_list.append(df_city1[level].sum() - df_moving_avg[level].sum())
|
|
# rate_list.append((df_city1[level].sum() - df_moving_avg[level].sum()) / df_city1[level].sum())
|
|
# resut_df = pd.DataFrame({'同期电量': tq_list, '预测电量': pred_list, '偏差': loss_list, '偏差率': rate_list},
|
|
# index=index_level)
|
|
# resut_df = pd.DataFrame({'预测电量': pred_list},index=index_level)
|
|
|
|
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市分压电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
|
|
engine='openpyxl') as writer:
|
|
resut_df.to_excel(writer, sheet_name=f'{city[4:6]}')
|
|
|
|
# excel_file = pd.ExcelFile(r'C:\Users\鸽子\Desktop\11月移动平均分压.xlsx')
|
|
# df1 = pd.read_excel(excel_file, sheet_name=1)
|
|
# df1.set_index(df1.columns[0], inplace=True)
|
|
# for sheet in excel_file.sheet_names[2:]:
|
|
# df = pd.read_excel(excel_file, sheet_name=sheet)
|
|
# df.set_index(df.columns[0], inplace=True)
|
|
# df1 += df
|
|
# df1['偏差'] = df1['同期电量'] - df1['预测电量']
|
|
# df1['偏差率'] = df1['偏差'] / df1['同期电量']
|
|
# df1.to_excel('移动平均_11月分压汇总.xlsx')
|
|
# print(df1)
|