{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import numpy as np\n", "import xlrd\n", "from plotly.graph_objs import Scatter, layout\n", "import plotly\n", "import plotly.offline as py\n", "import plotly.graph_objs as go\n", "import cufflinks as cf\n", "from urllib.request import urlopen\n", "import json\n", "import re\n", "cf.go_offline()###这两句是离线生成图片的设置\n", "cf.set_config_file(offline=True, world_readable=True)\n", "plotly.offline.init_notebook_mode(connected=True)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "alignmentgroup": "True", "bingroup": "x", "histfunc": "sum", "hovertemplate": "smoker=No
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of total_bill" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.express as px\n", "df = px.data.tips()\n", "fig = px.histogram(df, x=\"sex\", y=\"total_bill\",\n", " color='smoker', barmode='group',\n", " height=400)\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "indianred" }, "name": "MAE", "text": [ "7.724", "8.48" ], "textposition": "outside", "type": "bar", "x": [ "Linear Regression", "LR-LSTM model" ], "y": [ 7.724, 8.48 ] }, { "marker": { "color": "lightsalmon" }, "name": "RMSE", "text": [ "13.116", "18.736" ], "textposition": "outside", "type": "bar", "x": [ "Linear Regression", "LR-LSTM model" ], "y": [ 13.116, 18.736 ] } ], "layout": { "height": 600, "legend": { "title": { "text": "Type of error" } }, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, 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"gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "Errors on Gold data", "x": 0.5, "y": 0.9 }, "width": 500 } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.graph_objects as go\n", "animals=['Linear Regression', 'LR-LSTM model']\n", "y1, y2 = [7.724, 8.480], [13.116, 18.736]\n", "fig = go.Figure(data=[\n", " go.Bar(name='MAE', x=animals, y=y1, marker_color='indianred', text=y1, textposition=\"outside\"),\n", " go.Bar(name='RMSE', x=animals, y=y2, marker_color='lightsalmon', text=y2, textposition=\"outside\")])\n", "# Change the bar mode\n", "fig.update_layout(title={'text':'Errors on Gold data','y' : 0.9,'x' : 0.5, }, height=600, width=500, legend_title_text='Type of error')\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "interpreter": { "hash": "73e8fb81fc9d21637ba62ed4f9412d39843bbeeb61edb8163afd2f9314d52c65" }, "kernelspec": { "display_name": "Python 3.7.6 64-bit (system)", "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": "3.7.6" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }