Untitled.ipynb

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   "cell_type": "code",
   "source": "import pandas as pd",
   "execution_count": 1,
   "outputs": []
  },
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   "metadata": {
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   "cell_type": "code",
   "source": "import numpy as np",
   "execution_count": 2,
   "outputs": []
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   "cell_type": "code",
   "source": "df = pd.DataFrame(dict(galaxy_id=np.arange(10), quantity=np.random.uniform(10)))",
   "execution_count": 3,
   "outputs": []
  },
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   "cell_type": "code",
   "source": "df.head()",
   "execution_count": 4,
   "outputs": [
    {
     "output_type": "execute_result",
     "execution_count": 4,
     "data": {
      "text/plain": "   galaxy_id  quantity\n0          0  7.919644\n1          1  7.919644\n2          2  7.919644\n3          3  7.919644\n4          4  7.919644",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>galaxy_id</th>\n      <th>quantity</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>7.919644</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>7.919644</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>7.919644</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>7.919644</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>7.919644</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
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   "cell_type": "code",
   "source": "df.query('galaxy_id in (3,7)')",
   "execution_count": 5,
   "outputs": [
    {
     "output_type": "execute_result",
     "execution_count": 5,
     "data": {
      "text/plain": "   galaxy_id  quantity\n3          3  7.919644\n7          7  7.919644",
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