{
  "source": "live Code list",
  "fetched_at": "2026-10-22T10:42:43Z",
  "count": 151,
  "complete": true,
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    {
      "ref": "paulrohan2020/feature-engineering-naive-bayes-with-bag-of-words",
      "votes": 49
    },
    {
      "ref": "alitlekbai/simple-rnn-with-keras",
      "votes": 1
    },
    {
      "ref": "azhar05/donorschoose-project-proposal-by-md-azharuddin",
      "votes": 6
    },
    {
      "ref": "deepak939/donors-choose-with-gradientboostingclassifier",
      "votes": 4
    },
    {
      "ref": "sheetalkbc/dataanalysis-donorschoose",
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    },
    {
      "ref": "iacsddbda/neuralnetwork-approach",
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    },
    {
      "ref": "shubhamkc/eda-feature-engineering-and-xgb-lgb",
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    },
    {
      "ref": "anand0427/rnn-to-predict-project-proposal-acceptance",
      "votes": 2
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    {
      "ref": "puneeth987/donorschoose-org-application-screening",
      "votes": 1
    },
    {
      "ref": "neumatron11/jbj-python-demo",
      "votes": 0
    },
    {
      "ref": "maukag/donorschoose-script",
      "votes": 2
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    {
      "ref": "arpandas65/a-simple-xgboost-approach-to-solve-donorschoose",
      "votes": 5
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    {
      "ref": "trojonhorse98/knn-tsne",
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    {
      "ref": "thebratattack/exploratory-data-analysis",
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    {
      "ref": "timsikes/donors-choose-cleaned-up-working-version",
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    {
      "ref": "boomberung/eda-tf-idf-lightgbm",
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    {
      "ref": "zahoorahmad/exploring-donorchoose-org",
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      "ref": "zahoorahmad/donorschoose-exploratory-analysis",
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    {
      "ref": "prithiviraj/for-beginners-tfidf-logistic-regression",
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      "ref": "gauravtaneja/rf-example",
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    {
      "ref": "lmwaileong/eda-donors-org-application-screening",
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    {
      "ref": "anirudhvaranasi/donor-choose",
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    {
      "ref": "bogikidd/nltk-and-gru-on-donorschoose-org",
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    {
      "ref": "ashishpatel26/beginner-s-guide-to-capsule-networks",
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      "ref": "nafisur/beginner-s-guide-nn-with-multichannel-input",
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    {
      "ref": "xuyingh/first-kernel",
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    {
      "ref": "pulkitgarg33/project-apllication-screening-system",
      "votes": 1
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      "ref": "thesoum/donors-notebook",
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    {
      "ref": "timsikes/donors-choose-cleaned-up",
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    {
      "ref": "anuaspriya/donors-tensor",
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    {
      "ref": "rahulk29/donorschoose",
      "votes": 0
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      "ref": "jihyeseo/donorchoose-eda",
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      "ref": "jyotiska/jyotiska-donors-choose-project",
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    {
      "ref": "mvalexander/fork-of-donorschoose-full-cnn-yes-smote",
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      "ref": "mvalexander/donorschoose-mlnd-capstone-eda",
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      "ref": "estasney/donors-train2",
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      "ref": "nhrade/text-classification-using-word-embeddings",
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      "ref": "jordanrex/donorschoose-xgb-and-h2o-ensemble-in-r",
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      "ref": "justcliffsmith/logistic-regression-tfidf-with-explanations",
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      "ref": "estasney/donors-nb",
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    {
      "ref": "linwenxing/glove-vector-lstm",
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      "ref": "blastchar/donorschoose-some-water-lemon",
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      "ref": "estasney/learning-from-the-best-v4",
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      "ref": "dpeskov/natural-langage-processing-with-torchtext",
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      "ref": "mvalexander/donorschoose-models-ensemble",
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      "ref": "bigzhao/hierarchical-model-with-attention",
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      "ref": "shadowwarrior/1st-place-solution",
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      "ref": "pleonova/what-can-we-learn-from-the-essays",
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      "ref": "shadowwarrior/spellchecking-feature-improves-auc",
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      "ref": "anishjosh/donorschoose-org-application-screening",
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      "ref": "bricetaton/basic-bag-of-words",
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      "ref": "tommyod/mastering-the-basics-80-using-scikit-learn-v2-0",
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      "ref": "nujcharee/classification-with-spacy",
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      "ref": "holfyuen/too-simple-sometimes-naive-bayes",
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      "ref": "coronate/scoring-top-3",
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      "ref": "tetyanayatsenko/en-02",
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      "ref": "phustak/donors-choose-tensorflow-model",
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      "ref": "danlou7/logistic-regression-tf-idf-one-hot-metadata",
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      "ref": "tetyanayatsenko/ensembling-d50",
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      "ref": "rahulvks/lightgbm-and-tf-idf-with-bigram",
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      "ref": "amitkumarjaiswal/donorschoose-exploration-submission",
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      "ref": "emotionevil/dpcnn-pesudo-labeling",
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      "ref": "lsaa2014/comprehensive-eda-of-donorschoose-and-basic-ml",
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      "ref": "grjasewe/lgbm-with-selected-columns",
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      "ref": "arjundas/simple-eda-exploratory-donation-approval",
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    {
      "ref": "toorkp/dcds2018",
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      "ref": "qinhui1999/how-to-get-a-0-812x-score-on-a-single-model",
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      "ref": "shubham219/a-basic-starting-with-random-forest",
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    {
      "ref": "richarde/random-forest-with-50-reduction-in-training-time",
      "votes": 12
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      "ref": "shubham219/first-kernal",
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      "ref": "codename007/a-very-extensive-end-to-end-project-donorschoose",
      "votes": 247
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      "ref": "amitkumarjaiswal/feature-engineering-on-the-go",
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    {
      "ref": "blackbee2016/automation-of-feature-engineering",
      "votes": 25
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      "ref": "jmbull/nb-svm",
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      "ref": "ibrahimaptlo10/eda-using-tableau-and-word-counts",
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      "ref": "goragus/beginner-s-journey-to-ml-eda-tf-idf-lgbm",
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      "ref": "justcliffsmith/detailed-data-exploration-updated",
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      "ref": "pbnjeff/xgboosting-to-a-better-algorithm",
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    {
      "ref": "zahoorahmad/ensembling-with-logistic-regression-lb-81-947",
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      "ref": "jpnewmenji/eda-donorschoose-org-application-screening",
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      "ref": "fizzbuzz/the-all-in-one-model",
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      "ref": "safavieh/ultimate-feature-engineering-xgb-lgb-nn",
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    {
      "ref": "varmax/donorchoose-org-eda",
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      "ref": "zahoorahmad/grid-search-for-best-parameters",
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      "ref": "zahoorahmad/nlp-and-stacking-starter-dpcnn-lgb-lb0-80",
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      "ref": "tetyanayatsenko/power-64",
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    {
      "ref": "anqitu/lightlgb-with-text-and-self-engineered-features",
      "votes": 0
    },
    {
      "ref": "nicapotato/logit-stacker-with-power",
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      "ref": "blastchar/donorschoose-some-water",
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      "ref": "fizzbuzz/a-blend-with-logit",
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      "ref": "tetyanayatsenko/d-test-02",
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    {
      "ref": "cynthiacho/cynthiachoprojectsubmission",
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      "ref": "shadowwarrior/adversarial-validation-of-text",
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      "ref": "tantanchen/phillyr-1-loading-the-data",
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      "ref": "fizzbuzz/beginner-s-guide-to-capsule-networks",
      "votes": 762
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    {
      "ref": "shivamb/extensive-text-data-feature-engineering",
      "votes": 160
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    {
      "ref": "ahmedalesh/att-layer-for-keras-backend-using-tensorflow",
      "votes": 6
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    {
      "ref": "zahoorahmad/cleaning-and-selecting-features",
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      "ref": "matthewa313/naive-bayes-svm-on-vocabulary",
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      "ref": "matthewa313/ensembling-with-logistic-regression-lb-82-4",
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      "ref": "ianchute/baseline-model-bernoulli-naive-bayes-lb-0-68",
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      "ref": "anqitu/before-modelling-let-s-explore-and-visualize",
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      "ref": "nicapotato/abc-s-of-tf-idf-boosting-0-798",
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      "ref": "ibrahimaptlo10/probability-project-approved",
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    {
      "ref": "ftlftw/thinking-like-a-data-scientist-donorschoose-eda",
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      "ref": "tanank/data-exploration-and-random-forest-result",
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      "ref": "qinhui1999/deep-learning-is-all-you-need-lb-0-80x",
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      "ref": "manivelu05/simple-logistic-regression",
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      "ref": "fizzbuzz/a-pure-nlp-approach",
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      "ref": "vlasoff/beginner-s-guide-nn-with-multichannel-input",
      "votes": 190
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      "ref": "fizzbuzz/how-to-perform-rank-averaging",
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    {
      "ref": "fizzbuzz/lightgbm-and-nmf-starter-code",
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    {
      "ref": "amitkumarjaiswal/exploratory-analysis",
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    {
      "ref": "blasteraj/donorschoose-org-1",
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    {
      "ref": "satadru5/eda-and-ml-dl-modeling-with-donorschoose-data",
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    {
      "ref": "emotionevil/beginners-workflow-meanencoding-lgb-nn-ensemble",
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      "ref": "pecooper/pete-s-second-attempt",
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      "ref": "edzhang/quick-eda",
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    {
      "ref": "hoonkeng/how-to-get-81-gru-att-lgbm-tf-idf-eda",
      "votes": 119
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      "ref": "mutterberg/teacher-developed-donorschoose-analysis",
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      "ref": "ahmedalesh/glove-xgboost-and-lgbm",
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    {
      "ref": "jagangupta/understanding-approval-donorschoose-eda-fe-eli5",
      "votes": 63
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    {
      "ref": "vinodsundaram/simple-eda",
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    {
      "ref": "jgoldberg/donorschoose-eda-text-classification",
      "votes": 23
    },
    {
      "ref": "scirpus/target-encoding",
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    {
      "ref": "pecooper/xgboost-benchmark-v2",
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    },
    {
      "ref": "nvhbk16k53/simple-rnn-with-keras",
      "votes": 106
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    {
      "ref": "anu0012/eda-ensemble",
      "votes": 5
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    {
      "ref": "artgor/eda-feature-engineering-and-xgb-lgb",
      "votes": 193
    },
    {
      "ref": "sudalairajkumar/simple-eda-fe-notebook-donorschoose",
      "votes": 32
    },
    {
      "ref": "huguera/approve-me-donorschoose-eda",
      "votes": 7
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    {
      "ref": "blastchar/donorschoose-the-first-analysis",
      "votes": 2
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    {
      "ref": "danofer/donors-data-merge",
      "votes": 3
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    {
      "ref": "a45632/keras-baseline-feature-hashing-cnn-with-graph",
      "votes": 10
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    {
      "ref": "nicapotato/tf-idf-text-only",
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    {
      "ref": "nicapotato/tf-idf-and-features-logistic-regression",
      "votes": 25
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    {
      "ref": "CVxTz/simple-average-model",
      "votes": 16
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    {
      "ref": "CVxTz/keras-baseline-feature-hashing-cnn",
      "votes": 25
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    {
      "ref": "CVxTz/keras-baseline-feature-hashing-price-tfidf",
      "votes": 16
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    {
      "ref": "pbnjeff/donorschoose-previous-experience",
      "votes": 1
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    {
      "ref": "ambarish/eda-fe-xgb-glm-maps-donors-choose",
      "votes": 63
    },
    {
      "ref": "coronate/donorschoose-org-application-screening-with-keras",
      "votes": 5
    },
    {
      "ref": "pbnjeff/trainingdata-prefix-exploration",
      "votes": 0
    },
    {
      "ref": "pbnjeff/donorschoose-resources-exploration",
      "votes": 0
    },
    {
      "ref": "opanichev/lightgbm-and-tf-idf-starter",
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    },
    {
      "ref": "abhiyerasi/first-attempt-in-kaggle-need-suggestions",
      "votes": 3
    },
    {
      "ref": "mmi333/beat-the-benchmark-with-one-feature",
      "votes": 14
    },
    {
      "ref": "coronate/donorschoose-exploratory-analysis",
      "votes": 32
    },
    {
      "ref": "jmbull/xtra-credit-xgb-lgb-tfidf-feature-stacking",
      "votes": 35
    },
    {
      "ref": "headsortails/an-educated-guess-update-feature-engineering",
      "votes": 229
    },
    {
      "ref": "skleinfeld/getting-started-with-the-donorschoose-data-set",
      "votes": 214
    }
  ]
}