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        "value": "\nThe different methods can be visualized graphically:\n\n.. plot::\n\n    import matplotlib.pyplot as plt\n\n    a = np.arange(4)\n    p = np.linspace(0, 100, 6001)\n    ax = plt.gca()\n    lines = [\n        ('linear', '-', 'C0'),\n        ('inverted_cdf', ':', 'C1'),\n        # Almost the same as `inverted_cdf`:\n        ('averaged_inverted_cdf', '-.', 'C1'),\n        ('closest_observation', ':', 'C2'),\n        ('interpolated_inverted_cdf', '--', 'C1'),\n        ('hazen', '--', 'C3'),\n        ('weibull', '-.', 'C4'),\n        ('median_unbiased', '--', 'C5'),\n        ('normal_unbiased', '-.', 'C6'),\n        ]\n    for method, style, color in lines:\n        ax.plot(\n            p, np.percentile(a, p, method=method),\n            label=method, linestyle=style, color=color)\n    ax.set(\n        title='Percentiles for different methods and data: ' + str(a),\n        xlabel='Percentile',\n        ylabel='Estimated percentile value',\n        yticks=a)\n    ax.legend(bbox_to_anchor=(1.03, 1))\n    plt.tight_layout()\n    plt.show()"
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              "value": "equivalent to "
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              "value": "percentile(..., 50)"
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          "children": [
            {
              "__type": "Text",
              "__tag": 4046,
              "value": "equivalent to percentile, except q in the range [0, 1]."
            }
          ]
        }
      ],
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    "return_annotation": {
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  "references": [
    ".. [1] R. J. Hyndman and Y. Fan,",
    "   \"Sample quantiles in statistical packages,\"",
    "   The American Statistician, 50(4), pp. 361-365, 1996"
  ],
  "qa": "numpy:percentile",
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}