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@gusutabopb
Created April 9, 2018 06:48
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%load_ext pyq.magic\n",
"from pyq import q"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 基本操作"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"1 + 2"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"1 2 3 4"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"1 2 3 4"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 1 2 3 4 5 6 7 8 9"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"til 10"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"45"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"sum til 10"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### テーブル"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"c1 c2 c3\n",
"----------\n",
"1000 a 10\n",
"1001 b 20\n",
"1002 c 30\n",
"1003 a 40\n",
"1004 b 50\n",
"1005 a 60"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"t:([] c1:1000+til 6; c2:`a`b`c`a`b`a; c3:10*1+til 6)\n",
"t"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### q-sql"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"c1 val\n",
"--------\n",
"1003 80 \n",
"1004 100\n",
"1005 120"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%q\n",
"select c1, val:2*c3 from t where c1 > 1002"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Pythonへの変換\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pyq.K'>\n",
"1 2 3\n"
]
}
],
"source": [
"l = q(\"1 2 3\")\n",
"print(type(l))\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1, 2, 3]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(l)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def parse_row(row):\n",
" return {\n",
" 'c1': int(row['c1']),\n",
" 'c2': str(row['c2']),\n",
" 'c3': int(row['c3']),\n",
" }"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"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>c1</th>\n",
" <th>c2</th>\n",
" <th>c3</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1000</td>\n",
" <td>a</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1001</td>\n",
" <td>b</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1002</td>\n",
" <td>c</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1003</td>\n",
" <td>a</td>\n",
" <td>40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1004</td>\n",
" <td>b</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1005</td>\n",
" <td>a</td>\n",
" <td>60</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" c1 c2 c3\n",
"0 1000 a 10\n",
"1 1001 b 20\n",
"2 1002 c 30\n",
"3 1003 a 40\n",
"4 1004 b 50\n",
"5 1005 a 60"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.DataFrame([parse_row(i) for i in q('t')])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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