title: Index Match using python pandas
body: <p>I have the following 2 excel files:</p>
  <p>df1.xlsx:</p>
  <p>SETTLED_BILL_ID APPROVED_BY BILL_DESCRIPTION    BILLED_AMOUNT   BILL_CONTROL_NUMBER</p>
  <p>56006427    111 Loan Application    30000   991110749361</p>
  <p>55111860    111 Loan Application    30000   991110749370</p>
  <p>56606452    111 Loan Application    30000   991110749376</p>
  <p>55163447    111 Loan Application    30000   991110749378</p>
  <p>55213501    111 Loan Application    30000   991110749380</p>
  <p>55094012    111 Loan Application    30000   991110749381</p>
  <p>55739677    111 Loan Application    30000   991110749382</p>
  <p>55191825    111 Loan Application    30000   991110749383</p>
  <p>55952559    111 Loan Application    30000   991110749387</p>
  <p>58316565    111 Loan Application    30000   991110749390</p>
  <p>55094013    111 Loan Application    30000   991110749392</p>
  <p>55262079    111 Loan Application    30000   991110749394</p>
  <p>58148764    111 Loan Application    30000   991110749397</p>
  <p>55314522    111 Loan Application    30000   991110749399</p>
  <p>55192521    111 Loan Application    30000   991110749398</p>
  <p>55216501    111 Loan Application    30000   991110749400</p>
  <p>58769648    111 Loan Application    30000   991110749403</p>
  <p>55236840    111 Loan Application    30000   991110749404</p>
  <p>56062780    111 Loan Application    30000   991110770598</p>
  <p>58778154    111 Loan Application    30000   991110749406</p>
  <p>55596936    111 Loan Application    30000   991110749409</p>
  <p>and df2.xlsx</p>
  <p>id  appcategory sname   sex app_year    paid_status BILL_CONTROL_NUMBER</p>
  <p>206348  1   MSAGATI M   2020    1   991110749361</p>
  <p>206349  1   MWANSELE    M   2020    1   991110749370</p>
  <p>206350  1   MWAKO   M   2020    1   991110749376</p>
  <p>206351  1   DISMAS  M   2020    1   991110749364</p>
  <p>206352  1   NYANDWI M   2020    1   991110749365</p>
  <p>206353  1   THADEUS M   2020    1   991110749366</p>
  <p>206354  1   MAKOBA  M   2020    1   991110749367</p>
  <p>206355  1   MACHA   M   2020    1   991110749368</p>
  <p>206356  1   BAISHE  F   2020    1   991110749392</p>
  <p>206357  1   ANUWAR  M   2020    1   991110749394</p>
  <p>206358  1   SOSPETER    M   2020    1   991110749397</p>
  <p>206360  1   SHEMAHONGE  M   2020    1   991110749373
  206362  1   NGOGO   M   2020    1   991110749375</p>
  <p>206363  1   FARANGA M   2020    1   991110749376</p>
  <p>206364  1   ADOLF   M   2020    1   991110749377</p>
  <p>206365  1   ELIAS   M   2020    1   991110749378</p>
  <p>206367  1   SABRI   M   2020    1   991110749380</p>
  <p>206368  1   JOHN    M   2020    1   991110770598</p>
  <p>206369  1   LUGANGA M   2020    1   991110749406</p>
  <p>206370  1   HUCHE   M   2020    1   991110749383</p>
  <p>I want to check if all BILL_CONTROL_NUMBER from df1 are present in df2</p>
  <p>It can be solved using the Index + Match  functionality of excel. What shall be the best way to replicate it in Pandas.</p>
  <p>Desired Output: add a new column 'RESULTS'</p>
  <p>SETTLED_BILL_ID APPROVED_BY BILL_DESCRIPTION    BILLED_AMOUNT   BILL_CONTROL_NUMBER RESULTS</p>
  <p>56006427    111 Loan Application    30000   991110749361    TRUE</p>
  <p>55111860    111 Loan Application    30000   991110749370    TRUE</p>
  <p>56606452    111 Loan Application    30000   991110749376    TRUE</p>
  <p>55163447    111 Loan Application    30000   991110749378    TRUE</p>
  <p>55213501    111 Loan Application    30000   991110749380    TRUE</p>
  <p>55094012    111 Loan Application    30000   991110749381    FALSE</p>
  <p>55739677    111 Loan Application    30000   991110749382    FALSE</p>
  <p>55191825    111 Loan Application    30000   991110749383    TRUE</p>
  <p>55952559    111 Loan Application    30000   991110749387    FALSE</p>
  <p>58316565    111 Loan Application    30000   991110749390    FALSE</p>
  <p>55094013    111 Loan Application    30000   991110749392    TRUE</p>
  <p>55262079    111 Loan Application    30000   991110749394    TRUE</p>
  <p>58148764    111 Loan Application    30000   991110749397    TRUE</p>
  <p>55314522    111 Loan Application    30000   991110749399    FALSE</p>
  <p>55192521    111 Loan Application    30000   991110749398    FALSE</p>
  <p>55216501    111 Loan Application    30000   991110749400    FALSE</p>
  <p>58769648    111 Loan Application    30000   991110749403    FALSE</p>
  <p>55236840    111 Loan Application    30000   991110749404    FALSE</p>
  <p>56062780    111 Loan Application    30000   991110770598    TRUE</p>
  <p>58778154    111 Loan Application    30000   991110749406    TRUE</p>
  <p>55596936    111 Loan Application    30000   991110749409    FALSE</p>
  <p>Equivalent Excel formula <code>=NOT(ISERROR(MATCH(E2,$F$2:$F$21,0)))</code></p>
  <p><a href="https://docs.google.com/spreadsheets/d/1Rjsn-jotq96rYRbvlEKj8Xe7ug8BklwN/edit?usp=sharing&amp;ouid=100970845094450129298&amp;rtpof=true&amp;sd=true" rel="nofollow noreferrer">Link to df1</a></p>
  <p><a href="https://docs.google.com/spreadsheets/d/1KwiN5SvTCgZuN8xqdA8hAIr5wzZlvEi1/edit?usp=sharing&amp;ouid=100970845094450129298&amp;rtpof=true&amp;sd=true" rel="nofollow noreferrer">Link to df2</a></p>
  <p><a href="https://docs.google.com/spreadsheets/d/1DSkuj80zWWFBSl3GuiY1MpcE-QpD8VMJ/edit?usp=sharing&amp;ouid=100970845094450129298&amp;rtpof=true&amp;sd=true" rel="nofollow noreferrer">Link to desired output</a></p>