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碇 シンジン

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About 碇 シンジン

  • Birthday March 13

Title

  • Title
    Follower of the Fashionista

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  • Skype
    th
  • Twitter
    er
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    it
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    ir
  • YouTube
    RARARARARAardradtasrfuy
  • Steam ID
    r3r

Profile Information

  • Gender
    Male
  • Location
    Finland
  • Personal Motto
    RarityRarityRarityRarityRarityRarity
  • Interests
    RarityRarityRarityRarityRarityRarity

My Little Pony

  • Best Pony
    Rarity
  • Best Anthropomorphic FiM Race
    Unicorn

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Single Status Update

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  1.  

    aC(e){

    for (this.i = 0 ; this.i < e.length ; this.i++; ){

    var x = e.charAt(this.i); 

    var t = this.state.letters.findIndex(var j => j.name === x );

    If (t){

    this.state.letters[t].lkm++;

    this.uC();

    }

    else{

    this.state.letters.push({

    name: x,

    lkm: 1})

    this.uC();

    }

     

    }

    1. CypherHoof

      CypherHoof

      Cool. Might want to consider a case-insensitive count though, if you are doing the frequency analysis for a language fingerprint or to break a simple cipher....

    2. 碇 シンジン

      碇 シンジン

      scoured around 100k letters from random chinese articles excluding whitespaces

      1. ,: 5144 - 5.13% from all letters
      2. 的: 2792 - 2.79% from all letters
      3. 。: 1660 - 1.66% from all letters
      4. 人: 1601 - 1.60% from all letters
      5. 不: 1335 - 1.33% from all letters
      6. 一: 1301 - 1.30% from all letters
      7. 是: 1256 - 1.25% from all letters
      8. 有: 964 - 0.96% from all letters
      9. 0: 860 - 0.86% from all letters
      10. 你: 834 - 0.83% from all letters
      11. 自: 735 - 0.73% from all letters
      12. 了: 543 - 0.54% from all letters
      13. 生: 536 - 0.53% from all letters
      14. 在: 529 - 0.53% from all letters
      15. 己: 518 - 0.52% from all letters
      16. 个: 512 - 0.51% from all letters
      17. 就: 492 - 0.49% from all letters
      18. 心: 478 - 0.48% from all letters
      19. 要: 463 - 0.46% from all letters
      20. 为: 442 - 0.44% from all letters

    3. CypherHoof

      CypherHoof

      Cool. I haven't seen a frequency graph for chinese before, but am hoping you find it useful :)

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