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@theotheo
Created March 29, 2019 14:54
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Разные округления. Подробности: https://en.wikipedia.org/wiki/Rounding
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Создадим десять чисел "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2019-03-29T14:47:59.965794Z",
"start_time": "2019-03-29T14:47:59.611821Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5])"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np \n",
"\n",
"\n",
"original = np.arange(0, 10) + 0.5\n",
"\n",
"original"
]
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2019-03-29T14:49:36.555251Z",
"start_time": "2019-03-29T14:49:36.501650Z"
}
},
"source": [
"Округленим эти числа несколькими способами: \n",
"\n",
"- even_rounding -- до четного (3.5 --> 4, 4.5 --> 4)\n",
"- ceiling -- до целого вверх (3.5 --> 4, 4.5 --> 5)\n",
"- flooring -- до целого вниз (3.5 --> 3, 4.5 --> 4)\n",
"- original -- неокругленное\n",
"\n",
"И построим датафрейм"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2019-03-29T14:51:40.485379Z",
"start_time": "2019-03-29T14:51:40.380444Z"
}
},
"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>original</th>\n",
" <th>even_rounding</th>\n",
" <th>ceiling</th>\n",
" <th>flooring</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.5</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1.5</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2.5</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>5.5</td>\n",
" <td>6.0</td>\n",
" <td>6.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>6.5</td>\n",
" <td>6.0</td>\n",
" <td>7.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>7.5</td>\n",
" <td>8.0</td>\n",
" <td>8.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>8.5</td>\n",
" <td>8.0</td>\n",
" <td>9.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>9.5</td>\n",
" <td>10.0</td>\n",
" <td>10.0</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" original even_rounding ceiling flooring\n",
"0 0.5 0.0 1.0 0.0\n",
"1 1.5 2.0 2.0 1.0\n",
"2 2.5 2.0 3.0 2.0\n",
"3 3.5 4.0 4.0 3.0\n",
"4 4.5 4.0 5.0 4.0\n",
"5 5.5 6.0 6.0 5.0\n",
"6 6.5 6.0 7.0 6.0\n",
"7 7.5 8.0 8.0 7.0\n",
"8 8.5 8.0 9.0 8.0\n",
"9 9.5 10.0 10.0 9.0"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"\n",
"df = pd.DataFrame()\n",
"df['original'] = original\n",
"df['even_rounding'] = np.round(original)\n",
"df['ceiling'] = np.ceil(original)\n",
"df['flooring'] = np.floor(original)\n",
"\n",
"df"
]
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2019-03-29T14:52:34.637537Z",
"start_time": "2019-03-29T14:52:34.581445Z"
}
},
"source": [
"Просуммируем получившиеся ряды "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2019-03-29T14:52:40.348046Z",
"start_time": "2019-03-29T14:52:39.859081Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f0928984dd8>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df.cumsum().plot(figsize=(10, 10))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"ДЗ: сумма какого из рядов округленных чисел ближе к сумме неокругленных? "
]
}
],
"metadata": {
"jupytext": {
"main_language": "python",
"text_representation": {
"extension": ".md",
"format_name": "markdown",
"format_version": "1.0",
"jupytext_version": "0.8.5"
}
},
"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": "3.6.3"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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