title: how to retrieve sector and industry for a list of tickers with python?
body: <p>I have a list of tickers (below: tick1) that comes from the Earnings Report.
  I would like to add the &quot;shortname&quot;, &quot;sector&quot; and the &quot;industry&quot; next to the ticker while creating a dataframe.
  Unfortunately, the columns are always shuffeling up a bit and they are not matched properly. for instance: VFC --&gt; sector: technology; industry: Semiconductors, which is wrong. It should be sector: Consumer Cyclical; industry: Apparel Manufacturing</p>
  <p>Here is my code below: can you please help to adjust it?</p>
  <p>---tickers to be read---
  import yfinance as yf</p>
  <pre><code>with open(&quot;/Users/Doc/AB/Earnings/tickers.txt&quot;) as fh:
      tick1 = fh.read().split()
  </code></pre>
  <p>tickers in txt file
  ABOS
  ACRX
  ADI
  ADMP
  ADOCY
  AER
  AGYS
  AINV
  ALBO
  ALLT
  AMAT
  AMPS
  AOZOY
  ARCO
  AREC
  ARZGY
  ATAI
  AUTO
  AVAL
  AXDX
  BAH
  BBAR
  BBWI
  BHIL
  BJ
  BKYI
  BLBX
  BPCGY
  BPTH
  BRDS
  BZFD
  CAAP
  CAE
  CALT
  CCHWF
  CCSI
  CELC
  CFRHF
  CGEN
  CINT
  CLSN
  CMRX
  CRLBF
  CRXT
  CSCO
  CSWI
  CVSI
  CWBHF
  CWBR
  DAC
  DADA
  DE
  DECK
  DESP
  DLO
  DOYU
  DTST
  DUOT
  EAST
  EBR
  EBR.B
  EDAP
  ENJY
  EVTV
  EXP
  FATH
  FL
  FLO
  FSI
  FTK
  FUV
  FXLV
  GAN
  GBOX
  GDS
  GLBE
  GLOB
  GNLN
  GOED
  GOGL
  GRAB
  GRAMF
  GRCL
  HD
  HOOK
  HPK
  HUYA
  HWKN
  HYRE
  IBEX
  IGIC
  IKT
  IMPL
  INLB
  INLX
  INVO
  IONM
  IONQ
  IPW
  IPWR
  ISUN
  ITCTY
  JBI
  JD
  JHX
  JMIA
  KALA
  KBNT
  KEYS
  KMDA
  KORE
  KSLLF
  KSS
  KULR
  LOW
  LTRY
  LUNA
  LVLU
  MARK
  MBT
  MCG
  MCLD
  MDWD
  MDWT
  MIGI
  MIRO
  MNDY
  MNMD
  MNRO
  MSADY
  MSGM
  MUFG
  MVST
  NEXCF
  NGS
  NNOX
  NOVN
  NRDY
  NRGV
  NU
  NXGN
  OBSV
  OEG
  OMQS
  ONON
  PANW
  PASG
  PCYG
  PEAR
  PLNHF
  PLX
  PTE
  PTN
  PXS
  QIPT
  QRHC
  QTEK
  QUIK
  RCRT
  RDY
  REE
  REED
  REKR
  RKLB
  RMED
  RMTI
  ROST
  RSKD
  RYAAY
  SANW
  SCVL
  SDIG
  SE
  SHLS
  SHPW
  SHWZ
  SLGG
  SNPS
  SPRO
  SQM
  SRAD
  SSYS
  SUNL
  SUNW
  SUPV
  SYN
  SYRS
  TCEHY
  TCRT
  TCS
  TGI
  TGT
  THBRF
  TJX
  TKOMY
  TLLTF
  TME
  TRMR
  TSEM
  TSHA
  TTWO
  TXMD
  USWS
  VBLT
  VERB
  VEV
  VFC
  VIPS
  VJET
  VOXX
  VTRU
  VVOS
  VWE
  VYGVF
  VYNT
  WEBR
  WEDXF
  WEJO
  WIX
  WMS
  WMT
  WRBY
  WYY
  YALA
  YOU
  ZIM</p>
  <p>---adding the shortname, sector, industry ---
  from yahooquery import Ticker
  import pandas as pd</p>
  <pre><code>symbols = tick1
  
  tickers = Ticker(symbols, asynchronous=True)
  
  datasi = tickers.get_modules(&quot;summaryProfile quoteType&quot;)
  dfsi = pd.DataFrame.from_dict(datasi).T
  
  dataframes = [pd.json_normalize([x for x in dfsi[module] if isinstance(x, dict)]) for 
  module in ['summaryProfile', 'quoteType']]
  
  dfsi = pd.concat(dataframes, axis=1)
  dfsi
  </code></pre>