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davraamides/Rangebreaks.ipynb

Created January 23, 2023 19:02
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Jupyter notebook showing use of rangebreaks option in Plotly
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Rangebreaks.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 31,
"id": "da8e0a4c",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import plotly.graph_objects as go\n",
"import plotly.express as px\n",
"import plotly.io as plt_io"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "e7428601",
"metadata": {},
"outputs": [],
"source": [
"daydf = pd.read_csv('spy_day.csv', parse_dates=['date'])\n",
"mindf = pd.read_csv('spy_minute.csv', parse_dates=['date'])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "50947ae5",
"metadata": {},
"outputs": [],
"source": [
"colors = px.colors.qualitative.Plotly\n",
"\n",
"def style_and_save_chart(fig: go.Figure, title: str) -> go.Figure:\n",
" fig.update_traces(line=dict(color=colors[4], width=1), marker=dict(color=colors[4]))\n",
" fig.update_xaxes(showline=True, linewidth=1, linecolor='gray', mirror=True)\n",
" fig.update_yaxes(showline=True, linewidth=1, linecolor='gray', mirror=True)\n",
" fig.update_layout(\n",
" font_color=\"gray\",\n",
" title=title,\n",
" title_font_color=\"white\",\n",
" template='plotly_dark',\n",
" xaxis_title=\"Date\",\n",
" yaxis_title=\"Price\",\n",
" )\n",
" fig.write_image(title.replace(' ', '_').lower() + \".png\", scale=2)\n",
" return fig"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "fa2a316b",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"line": {
"color": "#FFA15A",
"width": 1
},
"marker": {
"color": "#FFA15A"
},
"mode": "lines",
"type": "scatter",
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"source": [
"df = daydf\n",
"fig = go.Figure()\n",
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"source": [
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],
"source": [
"df = daydf[(daydf.date >= '2021-05-24') & (daydf.date <= '2021-06-19')]\n",
"fig = go.Figure()\n",
"fig.add_trace(go.Scatter(x=df.date, y=df.close, mode='markers'))\n",
"fig.update_xaxes(\n",
" rangebreaks=[\n",
" dict(bounds=[\"sat\", \"mon\"]),\n",
" dict(values=[\"2021-05-31\"]) # Memorial Day\n",
" ]\n",
")\n",
"fig.update_layout(xaxis_tick0 = df['date'].iloc[0], xaxis_dtick=86400000)\n",
"style_and_save_chart(fig, title='Daily Price Data - Points No Gaps')"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "96b08a34",
"metadata": {},
"outputs": [
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" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; }); </script> </div>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = mindf\n",
"fig = go.Figure()\n",
"fig.add_trace(go.Scatter(x=df.date, y=df.close))\n",
"style_and_save_chart(fig, title='Minute Price Data')"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "3edd4603",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"line": {
"color": "#FFA15A",
"width": 1
},
"marker": {
"color": "#FFA15A",
"size": 1
},
"mode": "markers",
"type": "scatter",
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"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; }); </script> </div>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = mindf\n",
"fig = go.Figure()\n",
"fig.add_trace(go.Scatter(x=df.date, y=df.close, mode=\"markers\", marker=dict(size=1)))\n",
"style_and_save_chart(fig, title='Minute Price Data - Points')"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "8c1baee9",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"line": {
"color": "#FFA15A",
"width": 1
},
"marker": {
"color": "#FFA15A"
},
"type": "scatter",
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Raw
spy_day.csv
View raw

(Sorry about that, but we can’t show files that are this big right now.)

Raw
spy_minute.csv
View raw

(Sorry about that, but we can’t show files that are this big right now.)

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