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dropping entries snippets.
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Donne Martin 2015-01-29 15:16:25 -05:00
parent 46c1be9a02
commit 2398a0bf55
1 changed files with 182 additions and 3 deletions
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pandas/pandas.ipynb
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@ -1,7 +1,7 @@
{
"metadata": {
"name": "",
"signature": "sha256:a2c9f032efaa18f3ced5e2f10361f1c25cd23e7f29903af944a52c579903f03d"
"signature": "sha256:0dc910ada47612859f282813d751ef152a62e4d6493b0027ad17a368b35379a0"
},
"nbformat": 3,
"nbformat_minor": 0,
@ -16,7 +16,8 @@
"\n",
"* Series\n",
"* DataFrame\n",
"* Reindexing"
"* Reindexing\n",
"* Dropping Entries"
]
},
{
@ -2151,7 +2152,8 @@
"cell_type": "code",
"collapsed": false,
"input": [
"frame_3.ix[range(0, 7), ['state', 'pop', 'unempl', 'year']]"
"frame_6 = frame_3.ix[range(0, 7), ['state', 'pop', 'unempl', 'year']]\n",
"frame_6"
],
"language": "python",
"metadata": {},
@ -2242,6 +2244,183 @@
}
],
"prompt_number": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dropping Entries"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Drop rows from a Series or DataFrame:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"frame_7 = frame_6.drop([0, 1])\n",
"frame_7"
],
"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>state</th>\n",
" <th>pop</th>\n",
" <th>unempl</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> VA</td>\n",
" <td> 5.2</td>\n",
" <td> 6.0</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> MD</td>\n",
" <td> 4.0</td>\n",
" <td> 6.0</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> MD</td>\n",
" <td> 4.1</td>\n",
" <td> 6.1</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 4 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 46,
"text": [
" state pop unempl year\n",
"2 VA 5.2 6.0 2014\n",
"3 MD 4.0 6.0 2014\n",
"4 MD 4.1 6.1 2015\n",
"5 NaN NaN NaN NaN\n",
"6 NaN NaN NaN NaN\n",
"\n",
"[5 rows x 4 columns]"
]
}
],
"prompt_number": 46
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Drop columns from a DataFrame:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"frame_7 = frame_7.drop('unempl', axis=1)\n",
"frame_7"
],
"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>state</th>\n",
" <th>pop</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> VA</td>\n",
" <td> 5.2</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> MD</td>\n",
" <td> 4.0</td>\n",
" <td> 2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> MD</td>\n",
" <td> 4.1</td>\n",
" <td> 2015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 3 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 47,
"text": [
" state pop year\n",
"2 VA 5.2 2014\n",
"3 MD 4.0 2014\n",
"4 MD 4.1 2015\n",
"5 NaN NaN NaN\n",
"6 NaN NaN NaN\n",
"\n",
"[5 rows x 3 columns]"
]
}
],
"prompt_number": 47
}
],
"metadata": {}