Removed incomplete snippet for pandas idxmax causing an exception.

This commit is contained in:
Donne Martin 2015-02-28 18:37:44 -05:00
parent 1689cc3e76
commit 7586ae1b73

View File

@ -1,7 +1,7 @@
{
"metadata": {
"name": "",
"signature": "sha256:364642bdaf4f304a679c7bbde135fea5a7e31eb8da19fb9b24192091e3e34cb0"
"signature": "sha256:dcf024d8d7e8070e9c5c1ad5d846420549912ed82967bcd1d7ef1193a6eb6dd8"
},
"nbformat": 3,
"nbformat_minor": 0,
@ -5448,7 +5448,7 @@
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 120,
"prompt_number": 103,
"text": [
" state pop unempl year\n",
"0 VA 5.0 NaN 2012\n",
@ -5461,7 +5461,7 @@
]
}
],
"prompt_number": 120
"prompt_number": 103
},
{
"cell_type": "code",
@ -5475,7 +5475,7 @@
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 112,
"prompt_number": 104,
"text": [
"pop 23.4\n",
"unempl 18.1\n",
@ -5484,7 +5484,7 @@
]
}
],
"prompt_number": 112
"prompt_number": 104
},
{
"cell_type": "markdown",
@ -5505,7 +5505,7 @@
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 113,
"prompt_number": 105,
"text": [
"0 2017.0\n",
"1 2018.1\n",
@ -5518,7 +5518,7 @@
]
}
],
"prompt_number": 113
"prompt_number": 105
},
{
"cell_type": "markdown",
@ -5539,7 +5539,7 @@
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 115,
"prompt_number": 106,
"text": [
"0 NaN\n",
"1 NaN\n",
@ -5552,41 +5552,7 @@
]
}
],
"prompt_number": 115
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_6.idxmax()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "could not convert string to float: MD",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-117-eca0089f6d98>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf_6\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0midxmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/Users/dmartin/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc\u001b[0m in \u001b[0;36midxmax\u001b[0;34m(self, axis, skipna)\u001b[0m\n\u001b[1;32m 4197\u001b[0m \"\"\"\n\u001b[1;32m 4198\u001b[0m \u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis_number\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4199\u001b[0;31m \u001b[0mindices\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnanops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnanargmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskipna\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mskipna\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4200\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4201\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mNA\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mindices\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Users/dmartin/anaconda/lib/python2.7/site-packages/pandas/core/nanops.pyc\u001b[0m in \u001b[0;36mnanargmax\u001b[0;34m(values, axis, skipna)\u001b[0m\n\u001b[1;32m 432\u001b[0m \"\"\"\n\u001b[1;32m 433\u001b[0m values, mask, dtype, _ = _get_values(values, skipna, fill_value_typ='-inf',\n\u001b[0;32m--> 434\u001b[0;31m isfinite=True)\n\u001b[0m\u001b[1;32m 435\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 436\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_maybe_arg_null_out\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskipna\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Users/dmartin/anaconda/lib/python2.7/site-packages/pandas/core/nanops.pyc\u001b[0m in \u001b[0;36m_get_values\u001b[0;34m(values, skipna, fill_value, fill_value_typ, isfinite, copy)\u001b[0m\n\u001b[1;32m 157\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_values_from_object\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 158\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misfinite\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 159\u001b[0;31m \u001b[0mmask\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_isfinite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 160\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 161\u001b[0m \u001b[0mmask\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Users/dmartin/anaconda/lib/python2.7/site-packages/pandas/core/nanops.pyc\u001b[0m in \u001b[0;36m_isfinite\u001b[0;34m(values)\u001b[0m\n\u001b[1;32m 200\u001b[0m is_integer_dtype(values) or is_bool_dtype(values)):\n\u001b[1;32m 201\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m~\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misfinite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 202\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0;34m~\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misfinite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'float64'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 203\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 204\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: could not convert string to float: MD"
]
}
],
"prompt_number": 117
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
"prompt_number": 106
}
],
"metadata": {}