我可以通过一些我想隐藏其他两列的XXXX值来隐藏NAME列的数据，例如NAME列数据要隐藏其Address和Number数据的一些XXXX值
data = [['NISAMANEE ROWELL', '9198762345','qwerpoiuytr','98 Oxford Ave.Elk Grove Village, IL 60007'], ['ALICE BAISDEN', '8756342865','asdfghjklxc', '94 Valley Rd.Miami Gardens, FL 33056'], ['MARC COGNETTI', '9198762345', 'qwerasdfzxcv' , '221 Summer CircleGreer, SC 29650'], ['JOHNS HOPKINS HEALTHCARE', '9654987642','asdfghjkl', '8522 Pendergast AvenueVilla Park, IL 60181'], ['AMANDA PELLETIER', '9654987642','acderfgds', '8522 Pendergast AvenueVilla Park, IL 60181']]
df = pd.DataFrame(data, columns = ['Name', 'Number','Information','Address'])
df
def name(x):
x=x.title() # title the string
res=pos_tag(word_tokenize(x)) #tokenizing
arr_Val=[] # storing each word in this array
#exceptionList=['Healthcare','Lerner'] # exception list .. MUST UPDATE HERE !!!!
exc_list=['Mackesson Inc','Care','Healthcare','Henery Schien','Besse','LLC','CandP','INC','LTD','PHARMACY','PHARMACEUTICAL','HOSPITAL','COMPANY','ELECTRONICS','APP','VOLUNTEERS','SPECIALITIES','APPLIANCE','EXPRESS','MAGAZINE','SUPPLY','ENDOSCOPY','NETWandK','SCHOOL','AT&T','SOLUTIONS','SANITATION','SYSTEMS','COMPOUNDING','CLINIC','UTILITIES','DEPARTMENT','CREATIVE','PIN','employment','consultant','units','label','machine','anesthesia','services','medical','community','plaza','tech','bipolar','brand','commerce','testing','inspection','killer','plus','electric','division','diagnostic','materials','imaging','international','district','chamber','city','products','essentials','life','scissand','leasing','units','health','healthcare','surgical','enterprises','print','radiology','water','screens','telecom','neurology','biologicals','laundry','owners','law','offices','pharm','office','fire','safety','family','instruments','publishing','automation','center','plate','group','mall','diabetes','estate','electronic','fire','coffee','water','café','factandy','society','group','precision','oxygen','pizza','mills','lock','exterminate','fresh','graves','emeregency','care','security','empire','chemical','associate','mind','optics','coland','toolbox','properties','contract','agreement','learning','exchange','plumbing','leica','sales','shoppe','league','institute','thermo','gas','print','shack','manufacturing','colgate','environmental','neuro','state','board','children','journal','phone','USA','paper','urgent','radio','day','admin','level','bag','church','coast','account','financial','candpandation','sales','andthopedics','andtho','control','handler','king','test','filter','nandth','south','east','west','refrige','laband','bank','system','scientific','instrument','capital','pfizer','lab','labanda','alcon','group','vision','care','alarm','endo','stryke','realty','pest','optic','renewal','star','surgery','stuff','notes','tables','ssurgical','plasma','plaster','code','construction','notes','ink','park','power','gear','link','recandds','amazon','sweet','fish','food','sign','farm','concept','guard','county','prod','duplex','dental','safe','tax','shop','american','ameri','wandks','cloud','exam','therapy','optical','insurance','depot','doctands','telephone','distibutands','cable','comcast','image','first','choice','wear','energy','duke','nandthside','transcription','engineers','alarm','deli','universal','shield','cleaning','resources','int','direct','out','steak','americas','bread','panera','design','media','eye','kreme','krispy','verizon','one','procare','access','point','shield','total','display','pepsi','cola','distributand','consulting','cleaners','flags','mutual','comp','premier','pedaitrics','.com','enterprise','café','linen','opthalmic','upholstery','card','business','waste','innovations','architectural','agency','photography','exterminatands','times','global','house','ultrasound','aetna','flandist','scripture','steel','fast','vascular','corp','town','partnership','utility','advanced','disposal','bcbs','village','payments','corporation','benefit','service','court','dept','partnership','height','coporation','national','grid','fedex','xerox','walgreen','united','walmart','pse&g','communication','reliant','cross','cigna','terminix','staffing','office','admin','phone','expert','source','management','cash','plumber','springs','communications','expert','berkshire','staples','highmark','berkshire','of','Network','window','Locum','Delta','Greater','Treasurer','Investment','Elite','Explore','Foundation','Rentals','Rental','Textile','Municipal','Authority','Treat','Development','University','ACCRUENT','ROTO-ROOTER','KPMG','LLP','Fertilizing','Roofing','Central','Collection','UNIT','Aviation','Development','Acquisition','Square','Unlimited','light','bulbs','CO.','Doctors','Exterminators','Public','Utilities','Registration','Attorney']
exceptionList = [x.title() for x in exc_list]
for i in range( len (res)): # looping to store tokenized words into array
if( res[i][0] in exceptionList ):
return x
else:
arr_Val.append(res[i][0])
#print(res)
for i in range( len(res) ): # checking the POS as proper Noun (NNP)
if( res[i][1]=='NNP'):
length=len(res[i][0])
arr_Val[i]=str(length*'X' )
return(' '.join(arr_Val))
df['Name'] = df['Name'].astype(str).apply(name)
我想隐藏名称列包含XXXXX的两列地址和数字的行，列地址和数字数据也应以任意长度的XXXXX隐藏