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self-methods/pandas-dupulicated-function.ipynb Secret

Created December 31, 2020 06:44
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pandas-dupulicated-function.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"df = pd.DataFrame({\n",
" 'pre': ['東京都', '東京都', '神奈川県', '北海道', '北海道'],\n",
" 'name': ['saki', 'saki', 'takeshi', 'toshi', 'kei'],\n",
" 'age': [10, 10, 42, 29, 29]\n",
"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df"
]
},
{
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"outputs": [
{
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"0 False\n",
"1 True\n",
"2 False\n",
"3 False\n",
"4 False\n",
"dtype: bool"
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},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.duplicated()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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"0 False\n",
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"2 False\n",
"3 False\n",
"4 True\n",
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.duplicated(subset=['pre'])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
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"output_type": "execute_result"
}
],
"source": [
"df.duplicated(subset=['pre','age'])"
]
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"metadata": {},
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{
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}
],
"source": [
"df.duplicated(subset=['pre','age'], keep=False)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" <tbody>\n",
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" <td>北海道</td>\n",
" <td>kei</td>\n",
" <td>29</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" pre name age\n",
"0 東京都 saki 10\n",
"1 東京都 saki 10\n",
"3 北海道 toshi 29\n",
"4 北海道 kei 29"
]
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"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"duplicated_df = df[df.duplicated(subset=['pre'], keep=False)]\n",
"duplicated_df"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>神奈川県</td>\n",
" <td>takeshi</td>\n",
" <td>42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>北海道</td>\n",
" <td>toshi</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>北海道</td>\n",
" <td>kei</td>\n",
" <td>29</td>\n",
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"</table>\n",
"</div>"
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"text/plain": [
" pre name age\n",
"0 東京都 saki 10\n",
"2 神奈川県 takeshi 42\n",
"3 北海道 toshi 29\n",
"4 北海道 kei 29"
]
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"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
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" <th>2</th>\n",
" <td>神奈川県</td>\n",
" <td>takeshi</td>\n",
" <td>42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>北海道</td>\n",
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" pre name age\n",
"0 東京都 saki 10\n",
"2 神奈川県 takeshi 42\n",
"3 北海道 toshi 29"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.drop_duplicates(subset=['pre', 'age'])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
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" pre name age\n",
"2 神奈川県 takeshi 42"
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],
"source": [
"df.drop_duplicates(subset=['pre'], keep=False)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" <th>3</th>\n",
" <td>北海道</td>\n",
" <td>toshi</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>北海道</td>\n",
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" <td>29</td>\n",
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" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" pre name age\n",
"0 東京都 saki 10\n",
"2 神奈川県 takeshi 42\n",
"3 北海道 toshi 29\n",
"4 北海道 kei 29"
]
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"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.drop_duplicates(inplace=True)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" <td>saki</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>神奈川県</td>\n",
" <td>takeshi</td>\n",
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" <th>2</th>\n",
" <td>北海道</td>\n",
" <td>toshi</td>\n",
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" <tr>\n",
" <th>3</th>\n",
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"text/plain": [
" pre name age\n",
"0 東京都 saki 10\n",
"1 神奈川県 takeshi 42\n",
"2 北海道 toshi 29\n",
"3 北海道 kei 29"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.reset_index(drop=True,inplace=True)\n",
"df"
]
}
],
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