test_cases/bland_altman.ipynb

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    "def bland_altman(dataframe, column1:str, column2:str):\n",
    "    \"\"\"\n",
    "    Takes two specified columns from a given dataframe and applies Bland-Altman-Analysis to them.\n",
    "    Therefore, it adds two new columns, one called 'mean' containing the mean of the two corresponding values,\n",
    "    and one called 'diff' containing the difference between the two.\n",
    "    \"\"\"\n",
    "    import scipy\n",
    "    data1 = dataframe[column1]\n",
    "    data2 = dataframe[column2]\n",
    "    dataframe['mean'] = (data1 + data2) / 2\n",
    "    dataframe['diff'] = data2 - data1\n",
    "    return dataframe"
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    "def check(candidate):\n",
    "    import pandas as pd\n",
    "    import numpy as np\n",
    "    df = pd.DataFrame(\n",
    "        {\n",
    "         'a':[1,2,3,0],\n",
    "         'b':[2,2,3,6]\n",
    "        }\n",
    "    )\n",
    "\n",
    "    candidate(df, 'a', 'b')\n",
    "\n",
    "    assert len(df.columns) == 4\n",
    "    \n",
    "    mean_column = df['mean']\n",
    "    diff_column = df['diff']\n",
    "    \n",
    "    assert np.array_equal([1.5, 2, 3, 3], mean_column)\n",
    "    assert np.array_equal([1,  0,0, 6], diff_column) or \\\n",
    "           np.array_equal([-1, 0,0,-6], diff_column)"
   ]
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   "id": "577fd3b1-aa81-40c0-8a27-88e86ba48718",
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   "source": [
    "check(bland_altman)"
   ]
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   "source": []
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