get
/
pytorch
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

输出预测结果

Browse Source
main
鸽子 10 months ago
parent 6f21ab6485
commit 5e3d97c389
25 changed files with 72 additions and 87 deletions
Show Stats Download Patch File Download Diff File

BIN
入模数据/丽水.xlsx
View File

Binary file not shown.

BIN
入模数据/台州.xlsx
View File

Binary file not shown.

BIN
入模数据/嘉兴.xlsx
View File

Binary file not shown.

BIN
入模数据/宁波.xlsx
View File

Binary file not shown.

BIN
入模数据/杭州.xlsx
View File

Binary file not shown.

BIN
入模数据/温州.xlsx
View File

Binary file not shown.

BIN
入模数据/湖州.xlsx
View File

Binary file not shown.

BIN
入模数据/绍兴.xlsx
View File

Binary file not shown.

BIN
入模数据/舟山.xlsx
View File

Binary file not shown.

BIN
入模数据/衢州.xlsx
View File

Binary file not shown.

BIN
入模数据/金华.xlsx
View File

Binary file not shown.

BIN
各地级市日电量模型/jiaxing.bin
View File

Binary file not shown.

13
各地级市日电量模型/丽水.py
Unescape Escape View File

@ -83,20 +83,19 @@ print(goal2)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[16.2, 3.2, 0, 0, 1, 2023], [16.2, 6.5, 0, 0, 1, 2023],
[17.9, 6.4, 0, 0, 1, 2023], [15.9, 6.9, 0, 0, 1, 2023],
[15.7, 9.0, 0, 0, 1, 2023], [19.1, 7.4, 0, 3, 1, 2023],
[19.2, 8.1, 0, 3, 1, 2023], [13.4, 3.2, 0, 3, 1, 2023]
[11.8, 2.4, 0, 3, 1, 2023]
]) ])
# X_eval = np.array([[6.2,5.1,0,0,1,2023]]) # X_eval = np.array([[6.2,5.1,0,0,1,2023]])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28','2023-12-29','2023-12-30','2023-12-31' ]) result = pd.DataFrame(result, index=['2023-12-28','2023-12-29','2023-12-30','2023-12-31' ])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx',mode='a',if_sheet_exists='replace',engine='openpyxl') as writer: with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx',mode='a',if_sheet_exists='replace',engine='openpyxl') as writer:
result.to_excel(writer,sheet_name='丽水') result.to_excel(writer,sheet_name='丽水')

13
各地级市日电量模型/台州.py
Unescape Escape View File

@ -82,20 +82,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[17.3, 2.2, 0, 0, 1, 2023], [17.4, 5.4, 0, 0, 1, 2023],
[19, 5.5, 0, 0, 1, 2023], [15.8, 4.8, 0, 0, 1, 2023],
[16, 6.5, 0, 0, 1, 2023], [19.4, 8.9, 0, 3, 1, 2023],
[19.7, 7.9, 0, 3, 1, 2023], [13.3, 3.3, 0, 3, 1, 2023]
[11.9, 3.2, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='台州') result.to_excel(writer, sheet_name='台州')

13
各地级市日电量模型/嘉兴.py
Unescape Escape View File

@ -81,20 +81,19 @@ loaded_model.load_model('jiaxing.bin')
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[13.8, 2.1, 0, 0, 1, 2023], [10.7, 0.9, 0, 0, 1, 2023],
[12.1, 1.7, 0, 0, 1, 2023], [9.8, 4.5, 0, 0, 1, 2023],
[10.3, 3.0, 0, 0, 1, 2023], [11.2, 5.3, 0, 3, 1, 2023],
[12.1, 7.1, 0, 3, 1, 2023], [9.0, 2.1, 0, 3, 1, 2023]
[8.2, 1.3, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='嘉兴') result.to_excel(writer, sheet_name='嘉兴')

14
各地级市日电量模型/宁波.py
Unescape Escape View File

@ -80,21 +80,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[14.4, 3.7, 0, 0, 1, 2023],
[16.0, 3.0, 0, 0, 1, 2023], [12.6, 5.5, 0, 0, 1, 2023],
[14.8, 5.0, 0, 0, 1, 2023], [16.4, 7.6, 0, 3, 1, 2023],
[12.8, 4.8, 0, 0, 1, 2023], [10.9, 3.7, 0, 3, 1, 2023]
[20.9, 6.8, 0, 3, 1, 2023],
[9.5, 2.6, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='宁波') result.to_excel(writer, sheet_name='宁波')

13
各地级市日电量模型/杭州.py
Unescape Escape View File

@ -86,20 +86,19 @@ print(result_eval)
print('r2:', r2_score(y_test, y_pred)) print('r2:', r2_score(y_test, y_pred))
X_eval = np.array([ X_eval = np.array([
[14.9, 0.3, 0, 0, 1, 2023], [13.8, 1.4, 0, 0, 1, 2023],
[14.3, 1.2, 0, 0, 1, 2023], [10.1, 2.7, 0, 0, 1, 2023],
[10.6, 2.7, 0, 0, 1, 2023], [15.3, 6.3, 0, 3, 1, 2023],
[17.2, 2.7, 0, 3, 1, 2023], [12.2, 1.8, 0, 3, 1, 2023]
[10.7, 0.6, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='杭州') result.to_excel(writer, sheet_name='杭州')

13
各地级市日电量模型/温州.py
Unescape Escape View File

@ -83,20 +83,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[18, 3.3, 0, 0, 1, 2023], [19.0, 7.1, 0, 0, 1, 2023],
[18.8, 8.2, 0, 0, 1, 2023], [17.2, 8.2, 0, 0, 1, 2023],
[16.9, 11.2, 0, 0, 1, 2023], [19.9, 11.0, 0, 3, 1, 2023],
[20.7, 11.6, 0, 3, 1, 2023], [15.8, 4.2, 0, 3, 1, 2023]
[14.5, 3.3, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='温州') result.to_excel(writer, sheet_name='温州')

14
各地级市日电量模型/湖州.py
Unescape Escape View File

@ -83,21 +83,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[10.6, 1.7, 0, 0, 1, 2023],
[12.9, 2.1, 0, 0, 1, 2023], [9.1, 3.7, 0, 0, 1, 2023],
[11.7, 2.2, 0, 0, 1, 2023], [11, 5.1, 0, 3, 1, 2023],
[8, 1.9, 0, 0, 1, 2023], [11.0, 1.5, 0, 3, 1, 2023]
[13, 4.4, 0, 3, 1, 2023],
[9.7, 0.7, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='湖州') result.to_excel(writer, sheet_name='湖州')

14
各地级市日电量模型/绍兴.py
Unescape Escape View File

@ -79,21 +79,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[13.5, 3.2, 0, 0, 1, 2023],
[15.4, 0.1, 0, 0, 1, 2023], [12.3, 4.2, 0, 0, 1, 2023],
[14.2, 3.5, 0, 0, 1, 2023], [16.4, 6.2, 0, 3, 1, 2023],
[12.8, 4.6, 0, 0, 1, 2023], [12.2, 2.1, 0, 3, 1, 2023]
[19.7, 5.2, 0, 3, 1, 2023],
[10.9, 0.8, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'],result)) result = pd.concat((result_eval['eval'],result))
result.index = result.index.map(lambda x:str(x)[:10]) result.index = result.index.map(lambda x:str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='绍兴') result.to_excel(writer, sheet_name='绍兴')

13
各地级市日电量模型/舟山.py
Unescape Escape View File

@ -74,20 +74,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[15.1, 8.2, 0, 0, 1, 2023], [12.3, 8.4, 0, 0, 1, 2023],
[12.5, 8.5, 0, 0, 1, 2023], [13.3, 7.9, 0, 0, 1, 2023],
[12, 8.0, 0, 0, 1, 2023], [13.0, 10.6, 0, 3, 1, 2023],
[15.0, 10.0, 0, 3, 1, 2023], [10.5, 6.1, 0, 3, 1, 2023]
[9.3, 5.9, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'], result)) result = pd.concat((result_eval['eval'], result))
result.index = result.index.map(lambda x: str(x)[:10]) result.index = result.index.map(lambda x: str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='舟山') result.to_excel(writer, sheet_name='舟山')

13
各地级市日电量模型/衢州.py
Unescape Escape View File

@ -69,21 +69,20 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[15.0, 3.0, 0, 0, 1, 2023], [15.7, 4.5, 0, 0, 1, 2023],
[15.7, 5.1, 0, 0, 1, 2023], [16.0, 4.8, 0, 0, 1, 2023],
[15.2, 5.6, 0, 0, 1, 2023], [17.0, 7.4, 0, 3, 1, 2023],
[17.9, 6.8, 0, 3, 1, 2023], [12.9, 4.1, 0, 3, 1, 2023]
[12.0, 2.9, 0, 3, 1, 2023]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'],result)) result = pd.concat((result_eval['eval'],result))
result.index = result.index.map(lambda x:str(x)[:10]) result.index = result.index.map(lambda x:str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='衢州') result.to_excel(writer, sheet_name='衢州')

13
各地级市日电量模型/金华.py
Unescape Escape View File

@ -74,20 +74,19 @@ print(result_eval)
import numpy as np import numpy as np
X_eval = np.array([ X_eval = np.array([
[16.3, 2.5, 0, 0, 1], [16.8, 3.2, 0, 0, 1],
[16.9, 3.8, 0, 0, 1], [17.2, 5.3, 0, 0, 1],
[16.5, 6.2, 0, 0, 1], [17.2, 6.4, 0, 3, 1],
[18.8, 7.8, 0, 3, 1], [13.9, 4.0, 0, 3, 1]
[12.5, 2.8, 0, 3, 1]
]) ])
print(model.predict(X_eval)) print(model.predict(X_eval))
result = model.predict(X_eval) result = model.predict(X_eval)
result = pd.DataFrame(result, index=['2023-12-27', '2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31']) result = pd.DataFrame(result, index=['2023-12-28', '2023-12-29', '2023-12-30', '2023-12-31'])
result = pd.concat((result_eval['eval'],result)) result = pd.concat((result_eval['eval'],result))
result.index = result.index.map(lambda x:str(x)[:10]) result.index = result.index.map(lambda x:str(x)[:10])
result.columns = ['预测值'] result.columns = ['预测值']
print(result) print(result)
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\市区日电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
result.to_excel(writer, sheet_name='金华') result.to_excel(writer, sheet_name='金华')

6
浙江电压等级电量/分压_移动平均.py
Unescape Escape View File

@ -1,6 +1,6 @@
import pandas as pd import pandas as pd
df = pd.read_excel(r'C:\Users\鸽子\Desktop\zj20231228.xlsx', sheet_name=1) df = pd.read_excel(r'C:\Users\鸽子\Desktop\20231229.xlsx', sheet_name=1)
df['pt_date'] = pd.to_datetime(df['pt_date']) df['pt_date'] = pd.to_datetime(df['pt_date'])
# 移动平均 # 移动平均
@ -21,7 +21,7 @@ for city in df['city_name'].drop_duplicates():
# index_level.append(level) # index_level.append(level)
df_moving_avg = pd.DataFrame(df_city1[level], index=df_city1.index) df_moving_avg = pd.DataFrame(df_city1[level], index=df_city1.index)
future = pd.date_range(start='2023-12-27', periods=5, freq='D') future = pd.date_range(start='2023-12-28', periods=4, freq='D')
for date in future: for date in future:
df_moving_avg.loc[date, level] = df_moving_avg[-3:].mean().values df_moving_avg.loc[date, level] = df_moving_avg[-3:].mean().values
@ -38,7 +38,7 @@ for city in df['city_name'].drop_duplicates():
# index=index_level) # index=index_level)
# resut_df = pd.DataFrame({'预测电量': pred_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_1228.xlsx', mode='a', if_sheet_exists='replace', 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: engine='openpyxl') as writer:
resut_df.to_excel(writer, sheet_name=f'{city[4:6]}') resut_df.to_excel(writer, sheet_name=f'{city[4:6]}')

7
浙江行业电量/行业_移动平均.py
Unescape Escape View File

@ -1,12 +1,11 @@
import pandas as pd import pandas as pd
df = pd.read_excel(r'C:\Users\鸽子\Desktop\zj20231228.xlsx', sheet_name=2) df = pd.read_excel(r'C:\Users\鸽子\Desktop\20231229.xlsx', sheet_name=2)
df['stat_date'] = pd.to_datetime(df['stat_date']) df['stat_date'] = pd.to_datetime(df['stat_date'])
# 移动平均 # 移动平均
for city in df['city_name'].drop_duplicates(): for city in df['city_name'].drop_duplicates():
print(city)
df_city = df[df['city_name'] == city].set_index('stat_date').loc['2023-12'].sort_index() df_city = df[df['city_name'] == city].set_index('stat_date').loc['2023-12'].sort_index()
dict_big = {} dict_big = {}
dict_ok = {} dict_ok = {}
@ -20,7 +19,7 @@ for city in df['city_name'].drop_duplicates():
for industry in df_city.columns[2:]: for industry in df_city.columns[2:]:
# index_industry.append(industry) # index_industry.append(industry)
df_moving_avg = pd.DataFrame(df_city[industry], index=df_city.index) df_moving_avg = pd.DataFrame(df_city[industry], index=df_city.index)
future = pd.date_range(start='2023-12-27', periods=5, freq='D') future = pd.date_range(start='2023-12-28', periods=4, freq='D')
for date in future: for date in future:
df_moving_avg.loc[date, industry] = df_moving_avg[-3:].mean().values df_moving_avg.loc[date, industry] = df_moving_avg[-3:].mean().values
@ -32,7 +31,7 @@ for city in df['city_name'].drop_duplicates():
# pred_list.append(df_moving_avg[industry].sum()) # pred_list.append(df_moving_avg[industry].sum())
# loss_list.append(df_city1[industry].sum()-df_moving_avg[industry].sum()) # loss_list.append(df_city1[industry].sum()-df_moving_avg[industry].sum())
# rate_list.append((df_city1[industry].sum()-df_moving_avg[industry].sum())/df_city1[industry].sum()) # rate_list.append((df_city1[industry].sum()-df_moving_avg[industry].sum())/df_city1[industry].sum())
with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\行业电量预测_1228.xlsx', mode='a', if_sheet_exists='replace', with pd.ExcelWriter(r'C:\Users\鸽子\Desktop\行业电量预测_1229.xlsx', mode='a', if_sheet_exists='replace',
engine='openpyxl') as writer: engine='openpyxl') as writer:
resut_df.to_excel(writer, sheet_name=f'{city[4:6]}') resut_df.to_excel(writer, sheet_name=f'{city[4:6]}')

Write Preview
Loading…
Cancel
Save