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nagishin/sma_histgram.ipynb

Created January 28, 2022 02:05
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sma_histgram.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "SMA_histgram.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyMReMzKjW8hLO1aQe21cufR",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/nagishin/d71c8ecc3f93c6f679cbc7d28c269c37/sma_histgram.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"source": [
"!pip install mplfinance"
],
"metadata": {
"id": "SrPYx-BaLGpl"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# データ取得"
],
"metadata": {
"id": "U244DlMoYCyR"
}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "mJZQcgl1GZq6",
"outputId": "bc25dd1c-e539-4429-f920-0f1be6ce05da"
},
"outputs": [
{
"output_type": "display_data",
"data": {
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"</div>\n",
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"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-1663c8d7-1838-439c-9443-07f824ddec67');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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],
"text/plain": [
" datetime unixtime ... close volume\n",
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"1 2020-12-25 09:00:00+09:00 1608854400 ... 24728.5 2409655649\n",
"2 2020-12-26 09:00:00+09:00 1608940800 ... 26490.0 2293397405\n",
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"4 2020-12-28 09:00:00+09:00 1609113600 ... 27039.5 2222773553\n",
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"396 2022-01-24 09:00:00+09:00 1642982400 ... 36657.5 1752304000\n",
"397 2022-01-25 09:00:00+09:00 1643068800 ... 36949.0 895249700\n",
"398 2022-01-26 09:00:00+09:00 1643155200 ... 36819.0 1077510300\n",
"399 2022-01-27 09:00:00+09:00 1643241600 ... 37163.5 821052200\n",
"400 2022-01-28 09:00:00+09:00 1643328000 ... 36819.5 40426400\n",
"\n",
"[401 rows x 7 columns]"
]
},
"metadata": {}
}
],
"source": [
"import time\n",
"import requests\n",
"from collections import OrderedDict\n",
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"# BitMEX OHLCV 1D 400期間分を取得\n",
"resolution = 60 * 24 # minutes\n",
"count = 400\n",
"to_time = int(time.time())\n",
"from_time = to_time - count * resolution * 60\n",
"\n",
"url = f'https://www.bitmex.com/api/udf/history?symbol=XBTUSD&resolution={resolution}&from={from_time}&to={to_time}'\n",
"data = requests.get(url).json()\n",
"df_ohlcv = pd.DataFrame(OrderedDict(\n",
" unixtime=data['t'], open=data['o'], high=data['h'],\n",
" low=data['l'], close=data['c'], volume=data['v']))\n",
"\n",
"# 日付変換\n",
"df_ohlcv['datetime'] = pd.to_datetime(df_ohlcv['unixtime'], unit='s')\n",
"df_ohlcv = df_ohlcv.set_index('datetime')\n",
"df_ohlcv.index = df_ohlcv.index.tz_localize('UTC')\n",
"df_ohlcv.index = df_ohlcv.index.tz_convert('Asia/Tokyo')\n",
"df_ohlcv.reset_index(drop=False, inplace=True)\n",
"\n",
"display(df_ohlcv)"
]
},
{
"cell_type": "markdown",
"source": [
"# 移動平均計算"
],
"metadata": {
"id": "42M5xSuTYG97"
}
},
{
"cell_type": "code",
"source": [
"# 移動平均追加\n",
"df_ohlcv['sma10'] = df_ohlcv['close'].rolling(window=10, min_periods=1).mean()\n",
"df_ohlcv['sma20'] = df_ohlcv['close'].rolling(window=20, min_periods=1).mean()\n",
"\n",
"# 移動平均間の乖離率\n",
"df_ohlcv['diff_ratio'] = (df_ohlcv['sma10'] - df_ohlcv['sma20']).abs() / df_ohlcv['close']\n",
"\n",
"display(df_ohlcv)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "fSAovBfjHV6e",
"outputId": "785184df-78a4-44a8-c2c4-94340a5d532a"
},
"execution_count": 2,
"outputs": [
{
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"data": {
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" <th>close</th>\n",
" <th>volume</th>\n",
" <th>sma10</th>\n",
" <th>sma20</th>\n",
" <th>diff_ratio</th>\n",
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" <td>36657.5</td>\n",
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" <td>36260.0</td>\n",
" <td>36819.0</td>\n",
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" <td>0.054567</td>\n",
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" <tr>\n",
" <th>399</th>\n",
" <td>2022-01-27 09:00:00+09:00</td>\n",
" <td>1643241600</td>\n",
" <td>36819.0</td>\n",
" <td>37246.5</td>\n",
" <td>35514.0</td>\n",
" <td>37163.5</td>\n",
" <td>821052200</td>\n",
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" <td>0.061742</td>\n",
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" <td>2022-01-28 09:00:00+09:00</td>\n",
" <td>1643328000</td>\n",
" <td>37163.5</td>\n",
" <td>37444.0</td>\n",
" <td>36740.5</td>\n",
" <td>36819.5</td>\n",
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" <td>0.070801</td>\n",
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"<p>401 rows × 10 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6bf8ea1-03f0-4f54-a379-763e61b52554')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
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" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-f6bf8ea1-03f0-4f54-a379-763e61b52554 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-f6bf8ea1-03f0-4f54-a379-763e61b52554');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
],
"text/plain": [
" datetime unixtime ... sma20 diff_ratio\n",
"0 2020-12-24 09:00:00+09:00 1608768000 ... 23740.000000 0.000000\n",
"1 2020-12-25 09:00:00+09:00 1608854400 ... 24234.250000 0.000000\n",
"2 2020-12-26 09:00:00+09:00 1608940800 ... 24986.166667 0.000000\n",
"3 2020-12-27 09:00:00+09:00 1609027200 ... 25303.125000 0.000000\n",
"4 2020-12-28 09:00:00+09:00 1609113600 ... 25650.400000 0.000000\n",
".. ... ... ... ... ...\n",
"396 2022-01-24 09:00:00+09:00 1642982400 ... 41147.950000 0.038378\n",
"397 2022-01-25 09:00:00+09:00 1643068800 ... 40825.650000 0.045932\n",
"398 2022-01-26 09:00:00+09:00 1643155200 ... 40513.000000 0.054567\n",
"399 2022-01-27 09:00:00+09:00 1643241600 ... 40294.050000 0.061742\n",
"400 2022-01-28 09:00:00+09:00 1643328000 ... 40052.050000 0.070801\n",
"\n",
"[401 rows x 10 columns]"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# チャート表示"
],
"metadata": {
"id": "im7QtXEKYKdq"
}
},
{
"cell_type": "code",
"source": [
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import mplfinance.original_flavor as mpf\n",
"from matplotlib.ticker import FuncFormatter\n",
"\n",
"# 表示を直近150期間分に絞り込み\n",
"bars = 150\n",
"df = df_ohlcv[:bars].copy()\n",
"\n",
"# チャート領域マージン設定\n",
"matplotlib.rcParams['axes.xmargin'] = 0.0 # X軸\n",
"matplotlib.rcParams['axes.ymargin'] = 0.05 # Y軸\n",
"\n",
"# 分割プロット\n",
"fig, axes = plt.subplots(nrows=2, ncols=1, sharex=True, figsize=(16.0, 8.0))\n",
"plt.subplots_adjust(wspace=0.0, hspace=0.0) # 余白設定\n",
"\n",
"# タイトル\n",
"fig.suptitle('BitMEX 1D Candle / SMA Deviation Rate', size=16, weight=2, y=0.92)\n",
"\n",
"# メインチャート\n",
"ax0 = axes[0]\n",
"# ローソク足\n",
"mpf.candlestick2_ohlc(ax0,\n",
" opens=df['open'].values, highs=df['high'].values,\n",
" lows=df['low'].values, closes=df['close'].values,\n",
" width=0.8, colorup='#53B987', colordown='#EB4D5C')\n",
"# 移動平均\n",
"ax0.plot(df.index, df['sma10'].values, color='red')\n",
"ax0.plot(df.index, df['sma20'].values, color='blue')\n",
"ax0.grid(True, which='major', axis='both', linewidth=0.5)\n",
"\n",
"# サブチャート\n",
"ax1 = axes[1]\n",
"ax1.bar(df.index, df['diff_ratio'], width=0.8)\n",
"ax1.yaxis.set_major_formatter(FuncFormatter(lambda y, _: '{:.0%}'.format(y)))\n",
"ax1.grid(True, which='major', axis='both', linewidth=0.5)\n",
"\n",
"# X軸目盛り設定\n",
"unit_x = int(bars / 10)\n",
"xtick0 = unit_x - df['datetime'][0].day % unit_x\n",
"xticks = range(xtick0, len(df['datetime']), unit_x) # 表示位置配列\n",
"xlabels = [x.strftime('%y/%m/%d') for x in df['datetime']][xtick0::unit_x] # 表示ラベル配列\n",
"plt.xticks(xticks, xlabels)\n",
"\n",
"# チャート表示\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 506
},
"id": "6Do8l5K3I6Pa",
"outputId": "54db8c97-813e-429b-9b64-5e1a5587db66"
},
"execution_count": 3,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 1152x576 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
}
]
}
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