PS:非原创,根据大佬的课程 复现
#最近p个月,inv>0的月份数
def Num(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.where(df>0,1,0).sum(axis=1)
return inv+’_num’+str§,auto_value
#最近p个月,inv=0的月份数
def Nmz(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.where(df==0,1,0).sum(axis=1)
return inv+’_nmz’+str§,auto_value
#最近p个月,inv>0的月份数是否>=1
def Evr(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
arr=np.where(df>0,1,0).sum(axis=1)
auto_value = np.where(arr,1,0)
return inv+’_evr’+str§,auto_value
#最近p个月,inv均值
def Avg(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.nanmean(df,axis = 1 )
return inv+’_avg’+str§,auto_value
#最近p个月,inv和
def Tot(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.nansum(df,axis = 1)
return inv+’_tot’+str§,auto_value
#最近(2,p+1)个月,inv和
def Tot2T(inv,p):
df=data.loc[:,inv+‘2’:inv+str(p+1)]
auto_value=df.sum(1)
return inv+’_tot2t’+str§,auto_value
#最近p个月,inv最大值
def Max(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.nanmax(df,axis = 1)
return inv+’_max’+str§,auto_value
#最近p个月,inv最小值
def Min(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
auto_value=np.nanmin(df,axis = 1)
return inv+’_min’+str§,auto_value
#最近p个月,最近一次inv>0到现在的月份数
def Msg(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
df_value=np.where(df>0,1,0)
auto_value=[]
for i in range(len(df_value)):
row_value=df_value[i,:]
if row_value.max()<=0:
indexs=‘0’
auto_value.append(indexs)
else:
indexs=1
for j in row_value:
if j>0:
break
indexs+=1
auto_value.append(indexs)
return inv+’_msg’+str§,auto_value
#最近p个月,最近一次inv=0到现在的月份数
def Msz(inv,p):
df=data.loc[:,inv+‘1’:inv+str§]
df_value=np.wh