Build feature analyzer in Python

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#183 opened on Sep 2, 2024 2 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty: 4/5
Estimated time: 3-5 days
Newbie friendliness: 35/100

Issue type: Feature
Clarity: Mostly clear
Activity status: Stale
Tech stack: python
Domain: api, data

Research direction

Start by tracing the existing /data/features/{id} endpoint and how feature metadata is currently obtained. Use the example response as the expected output, including feature names, types, flags, nominal values, and missing-value counts. Done means the endpoint exposes the requested basic feature information.

Written by the indexing model from the issue text.

Description

wontfix

Create a Python-based feature analyzer that calculates basic feature information available through /data/features/{id} endpoint, e.g.:

{
  "data_features": {
    "feature": [
      {
        "index": "0",
        "name": "sepallength",
        "data_type": "numeric",
        "is_target": "false",
        "is_ignore": "false",
        "is_row_identifier": "false",
        "number_of_missing_values": "0"
      },
      {
        "index": "1",
        "name": "sepalwidth",
        "data_type": "numeric",
        "is_target": "false",
        "is_ignore": "false",
        "is_row_identifier": "false",
        "number_of_missing_values": "0"
      },
      {
        "index": "2",
        "name": "petallength",
        "data_type": "numeric",
        "is_target": "false",
        "is_ignore": "false",
        "is_row_identifier": "false",
        "number_of_missing_values": "0"
      },
      {
        "index": "3",
        "name": "petalwidth",
        "data_type": "numeric",
        "is_target": "false",
        "is_ignore": "false",
        "is_row_identifier": "false",
        "number_of_missing_values": "0"
      },
      {
        "index": "4",
        "name": "class",
        "data_type": "nominal",
        "nominal_value": [
          "Iris-setosa",
          "Iris-versicolor",
          "Iris-virginica"
        ],
        "is_target": "true",
        "is_ignore": "false",
        "is_row_identifier": "false",
        "number_of_missing_values": "0"
      }
    ]
  }
}

Dominant language: Python
Stars: 16
Forks: 50
PR merge metrics: No merged PRs in 30d

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