周报Python【未完】

#coding:utf-8
import pandas as pd
import numpy as np

np.set_printoptions(suppress=True)#不以科学计数法输出
pd.set_option('display.width', None)
pd.set_option('display.max_columns', None)

zb = pd.read_excel(r'C:\Users\Administrator\Desktop\ZB0914.xlsx')
print('数据帧前五行：\n{}\n'.format(zb.head()))

#可拆分
#func=['count','sum','max']
#result = grouped['申请ID','通过金额'].agg(func)
#-------可拆分-----可整合
#grouped = df.groupby(['城市','产品'])#行标签
#result = grouped.agg({'申请ID':'count','通过金额':'sum'})#根据不同计算方法根据列名提取对应值
#print (result)

'''-----------------------------------------------新增逾期'''
zb1 = zb[(zb['M2']==1)&(zb['BillMonth']=='2018-09-10')]#条件筛选
zb_t=pd.pivot_table(zb1,
              index=['ORG','NAME'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print('新增逾期:\n{}\n'.format(zb_t))

'''------------------------------------------------逾期应偿'''
#逾期应偿
zb2 = zb[(zb['M2']!=0)&(zb['BillMonth']<='2018-09-10')]#条件筛选
zb2_t=pd.pivot_table(zb2,
              index=['ORG','NAME'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print('逾期应偿:\n{}\n'.format(zb2_t))

'''------------------------------------------------剩余应偿'''
zb3 = zb[zb['M2']!=0]#条件筛选
zb3_t=pd.pivot_table(zb3,
              index=['ORG','NAME'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print('剩余应偿:\n{}\n'.format(zb3_t))

'''------------------------------------------------vintage'''
#累计剩余应偿本金
zbM0_M7 = pd.pivot_table(zb,
              index=['Vintage'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print(zbM0_M7)

zb_M1_M7 = zb[zb['M2']!=0]#条件筛选
zb_M1_M7_t=pd.pivot_table(zb_M1_M7,
              index=['Vintage'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print(zb_M1_M7_t)

zb_M4_M7 = zb[(zb['M2']>=4)&(zb['M2']<=7)]#条件筛选
zb_M4_M7_t = pd.pivot_table(zb_M4_M7,
              index=['Vintage'],
               values=['Prin'],
               aggfunc=np.sum, margins = True)
print(zb_M4_M7_t)