|
|
|
|
import os
|
|
|
|
|
|
|
|
|
|
import numpy as np
|
|
|
|
|
import pandas as pd
|
|
|
|
|
n1 = np.array([[1,1,1]])
|
|
|
|
|
n2 = np.array([1,1,1]).reshape(1,-1)
|
|
|
|
|
print(n2)
|
|
|
|
|
n2 = np.array([]).reshape(3,-1)
|
|
|
|
|
|
|
|
|
|
print(np.max([[1,2,3],[4,5,6]]))
|
|
|
|
|
|
|
|
|
|
file_dir = r'C:\Users\user\Desktop\浙江各地市分电压日电量数据'
|
|
|
|
|
df = pd.read_excel(r'C:\Users\user\Desktop\浙江省各地市日电量及分压数据21-23年.xlsx',sheet_name=1)
|
|
|
|
|
df.columns = df.columns.map(lambda x:x.strip())
|
|
|
|
|
for city in df['地市'].drop_duplicates():
|
|
|
|
|
df_city = df[df['地市']== city]
|
|
|
|
|
df_city['stat_date'] = df_city['stat_date'].map(lambda x:x.strip())
|
|
|
|
|
df_city['stat_date'] = pd.to_datetime(df_city['stat_date'],format='%Y-%m-%d')
|
|
|
|
|
df_city = df_city[df_city.columns[:-1]]
|
|
|
|
|
df_city.sort_values(by='stat_date',ascending=True,inplace=True)
|
|
|
|
|
df_city['stat_date'] = df_city['stat_date'].astype('str')
|
|
|
|
|
df_city.to_excel(fr'C:\Users\user\Desktop\浙江各地市分电压日电量数据\{city}.xlsx',index=False)
|
|
|
|
|
# file_Dir = r'C:\Users\鸽子\Desktop\浙江各地市行业电量数据'
|
|
|
|
|
# for excel in os.listdir(file_Dir):
|
|
|
|
|
# df1 = pd.read_excel(r'C:\Users\鸽子\Desktop\浙江各地市日电量数据-27-28).xlsx',sheet_name=1)
|
|
|
|
|
# df1.columns = df1.columns.map(lambda x:x.strip())
|
|
|
|
|
# df2 = pd.read_excel(os.path.join(file_Dir,excel))
|
|
|
|
|
# df2['地市'] = df2['地市'].map(lambda x:x.strip())
|
|
|
|
|
# city = df2['地市'].iloc[0]
|
|
|
|
|
# col_list = df2.columns
|
|
|
|
|
# df1 = df1[col_list]
|
|
|
|
|
# df1 = df1[(df1['stat_date']==20231028)&(df1['地市']==city)]
|
|
|
|
|
# df1['stat_date'] = pd.to_datetime(df1['stat_date'],format='%Y%m%d')
|
|
|
|
|
# df2 = pd.concat((df2,df1),ignore_index=True)
|
|
|
|
|
# df2.to_excel(fr'C:\Users\鸽子\Desktop\浙江各地市行业电量数据\{city}.xlsx')
|
|
|
|
|
|
