Print mixed dtypes in columns of DataFrame

gistfile1.txt

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   "cells": [
    {
     "cell_type": "code",
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     "input": [
      "import numpy as np\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Consider the following simple DataFrame"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df  = pd.DataFrame([[1,2],[3,4]])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It has the following types:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.dtypes"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
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       "prompt_number": 3,
       "text": [
        "0    int64\n",
        "1    int64\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "However, if we append another row that contain a float"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2 = pd.concat([df, pd.DataFrame([[10.,11]])])\n",
      "df2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>0</th>\n",
        "      <th>1</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  1</td>\n",
        "      <td>  2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  3</td>\n",
        "      <td>  4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 10</td>\n",
        "      <td> 11</td>\n",
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        "  </tbody>\n",
        "</table>\n",
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       "prompt_number": 4,
       "text": [
        "    0   1\n",
        "0   1   2\n",
        "1   3   4\n",
        "0  10  11"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Then, we see that the type of the first column is changed to a float"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df2.dtypes"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "0    float64\n",
        "1      int64\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is not so bad... at the momment. But if we change the DataFrame further:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df3 = pd.concat([df, pd.DataFrame([[10.1,11]])])\n",
      "df3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>0</th>\n",
        "      <th>1</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  1.0</td>\n",
        "      <td>  2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  3.0</td>\n",
        "      <td>  4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 10.1</td>\n",
        "      <td> 11</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
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       "prompt_number": 6,
       "text": [
        "      0   1\n",
        "0   1.0   2\n",
        "1   3.0   4\n",
        "0  10.1  11"
       ]
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     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is already annoying. The integers (that were casted into floats) are now printed as floats. A workaround is to define a printing function:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def printFloat(x):\n",
      "    if np.modf(x)[0] == 0:\n",
      "        return str(int(x))\n",
      "    else:\n",
      "        return str(x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "and pass it to Pandas:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.options.display.float_format = printFloat"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, printing df3 yields:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>0</th>\n",
        "      <th>1</th>\n",
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        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>   1</td>\n",
        "      <td>  2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>   3</td>\n",
        "      <td>  4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>10.1</td>\n",
        "      <td> 11</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
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       "prompt_number": 9,
       "text": [
        "     0   1\n",
        "0    1   2\n",
        "1    3   4\n",
        "0 10.1  11"
       ]
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