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coal-price-forecast

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Add box_cox.ipynb

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  1. box_cox.ipynb +1334 -24
box_cox.ipynb CHANGED
@@ -2,20 +2,57 @@
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
- "execution_count": 8,
6
  "metadata": {},
7
  "outputs": [],
8
  "source": [
9
  "# Import packages\n",
10
  "import plotly.express as px\n",
11
  "import pandas as pd\n",
 
12
  "# Import the transform\n",
13
  "from scipy.stats import boxcox"
14
  ]
15
  },
16
  {
17
  "cell_type": "code",
18
- "execution_count": 9,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "metadata": {},
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  "outputs": [],
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  "source": [
@@ -25,7 +62,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 2,
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  "metadata": {},
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  "outputs": [
31
  {
@@ -131,7 +168,7 @@
131
  "[144 rows x 2 columns]"
132
  ]
133
  },
134
- "execution_count": 2,
135
  "metadata": {},
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  "output_type": "execute_result"
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  }
@@ -142,7 +179,7 @@
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  },
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  {
144
  "cell_type": "code",
145
- "execution_count": 3,
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  "metadata": {},
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  "outputs": [
148
  {
@@ -162,7 +199,7 @@
162
  "Name: Month, Length: 144, dtype: object"
163
  ]
164
  },
165
- "execution_count": 3,
166
  "metadata": {},
167
  "output_type": "execute_result"
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  }
@@ -173,24 +210,24 @@
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  },
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  {
175
  "cell_type": "code",
176
- "execution_count": 4,
177
  "metadata": {},
178
  "outputs": [],
179
  "source": [
180
  "# def plotting(title, data, x, y, x_label, y_label, text=False, lam=None):\n",
181
- "title=\"Airline Passengers\"\n",
182
- "data=data\n",
183
- "x=\"Month\"\n",
184
- "y=\"#Passengers\"\n",
185
- "x_label=\"Date\"\n",
186
- "y_label=\"Passengers\"\n",
187
- "text=False\n",
188
- "lam=None"
189
  ]
190
  },
191
  {
192
  "cell_type": "code",
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- "execution_count": 5,
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  "metadata": {},
195
  "outputs": [],
196
  "source": [
@@ -200,7 +237,7 @@
200
  },
201
  {
202
  "cell_type": "code",
203
- "execution_count": 6,
204
  "metadata": {},
205
  "outputs": [
206
  {
@@ -1377,7 +1414,7 @@
1377
  },
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  {
1379
  "cell_type": "code",
1380
- "execution_count": 7,
1381
  "metadata": {},
1382
  "outputs": [
1383
  {
@@ -2673,7 +2710,7 @@
2673
  }
2674
  ],
2675
  "source": [
2676
- "boxcox(data['#Passengers'])"
2677
  ]
2678
  },
2679
  {
@@ -2683,18 +2720,1291 @@
2683
  "outputs": [],
2684
  "source": [
2685
  "# Apply box-cox transform and plot it\n",
2686
- "data['Passengers_box_cox'], lam = boxcox(data['#Passengers'])"
2687
  ]
2688
  },
2689
  {
2690
  "cell_type": "code",
2691
- "execution_count": null,
2692
  "metadata": {},
2693
- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
2694
  "source": [
2695
- "plotting(title='Airline Passengers', data=data, x='Month', y='Passengers_box_cox',\n",
2696
- " x_label='Date', y_label='Passengers<br>Box-Cox Transform', text=True, lam=lam)"
2697
  ]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ],
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  "metadata": {
 
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  "cells": [
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  {
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  "cell_type": "code",
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+ "execution_count": 1,
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  "metadata": {},
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  "outputs": [],
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  "source": [
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  "# Import packages\n",
10
  "import plotly.express as px\n",
11
  "import pandas as pd\n",
12
+ "\n",
13
  "# Import the transform\n",
14
  "from scipy.stats import boxcox"
15
  ]
16
  },
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  {
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  "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def plotting(title, data, x, y, x_label, y_label, text=False, lam=None):\n",
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+ " \"\"\"General function to plot the passenger data.\"\"\"\n",
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+ " fig = px.line(data, x=data[x], y=data[y], labels={x: x_label, y: y_label})\n",
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+ "\n",
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+ " fig.update_layout(\n",
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+ " template=\"simple_white\",\n",
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+ " font=dict(size=18),\n",
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+ " title_text=title,\n",
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+ " width=650,\n",
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+ " title_x=0.5,\n",
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+ " height=400,\n",
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+ " )\n",
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+ "\n",
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+ " if text:\n",
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+ " fig.add_annotation(\n",
38
+ " x=\"1952-12-20\",\n",
39
+ " y=10,\n",
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+ " text=f\"Lambda = {lam:.3f}\",\n",
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+ " align=\"left\",\n",
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+ " yanchor=\"bottom\",\n",
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+ " showarrow=False,\n",
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+ " font=dict(size=20, color=\"black\", family=\"Courier New, monospace\"),\n",
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+ " bordercolor=\"black\",\n",
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+ " borderwidth=2,\n",
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+ " bgcolor=\"white\",\n",
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+ " )\n",
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+ "\n",
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+ " fig.show()"
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+ ]
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+ },
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+ "cell_type": "code",
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+ "execution_count": 3,
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  "metadata": {},
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  "cell_type": "code",
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  {
 
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  "[144 rows x 2 columns]"
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  ]
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  "output_type": "execute_result"
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  "cell_type": "code",
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  {
 
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  "Name: Month, Length: 144, dtype: object"
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  ]
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  "output_type": "execute_result"
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212
  "cell_type": "code",
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+ "execution_count": 6,
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  "metadata": {},
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  "outputs": [],
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  "source": [
217
  "# def plotting(title, data, x, y, x_label, y_label, text=False, lam=None):\n",
218
+ "title = \"Airline Passengers\"\n",
219
+ "data = data\n",
220
+ "x = \"Month\"\n",
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+ "y = \"#Passengers\"\n",
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+ "x_label = \"Date\"\n",
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+ "y_label = \"Passengers\"\n",
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+ "text = False\n",
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+ "lam = None"
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  ]
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 7,
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 8,
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  "metadata": {},
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  {
 
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  {
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  "cell_type": "code",
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+ "execution_count": 9,
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  "metadata": {},
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  "outputs": [
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  {
 
2710
  }
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  ],
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  "source": [
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+ "boxcox(data[\"#Passengers\"])"
2714
  ]
2715
  },
2716
  {
 
2720
  "outputs": [],
2721
  "source": [
2722
  "# Apply box-cox transform and plot it\n",
2723
+ "data[\"Passengers_box_cox\"], lam = boxcox(data[\"#Passengers\"])"
2724
  ]
2725
  },
2726
  {
2727
  "cell_type": "code",
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+ "execution_count": 13,
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  "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/plain": [
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+ "0.14802256973464573"
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+ ]
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+ "plotlyServerURL": "https://plot.ly"
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+ "hovertemplate": "Date=%{x}<br>Passengers<br>Box-Cox Transform=%{y}<extra></extra>",
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+ },
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+ "geo": {
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+ "landcolor": "white",
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+ },
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+ "gridcolor": "rgb(232,232,232)",
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+ }
3894
+ },
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+ "shapedefaults": {
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+ "line": {
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+ },
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+ "opacity": 0.3
3901
+ },
3902
+ "ternary": {
3903
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3904
+ "gridcolor": "rgb(232,232,232)",
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+ "linecolor": "rgb(36,36,36)",
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+ "showgrid": false,
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+ "showline": true,
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+ },
3910
+ "baxis": {
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+ "gridcolor": "rgb(232,232,232)",
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+ "linecolor": "rgb(36,36,36)",
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+ "showgrid": false,
3914
+ "showline": true,
3915
+ "ticks": "outside"
3916
+ },
3917
+ "bgcolor": "white",
3918
+ "caxis": {
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+ "gridcolor": "rgb(232,232,232)",
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+ "linecolor": "rgb(36,36,36)",
3921
+ "showgrid": false,
3922
+ "showline": true,
3923
+ "ticks": "outside"
3924
+ }
3925
+ },
3926
+ "title": {
3927
+ "x": 0.05
3928
+ },
3929
+ "xaxis": {
3930
+ "automargin": true,
3931
+ "gridcolor": "rgb(232,232,232)",
3932
+ "linecolor": "rgb(36,36,36)",
3933
+ "showgrid": false,
3934
+ "showline": true,
3935
+ "ticks": "outside",
3936
+ "title": {
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+ "standoff": 15
3938
+ },
3939
+ "zeroline": false,
3940
+ "zerolinecolor": "rgb(36,36,36)"
3941
+ },
3942
+ "yaxis": {
3943
+ "automargin": true,
3944
+ "gridcolor": "rgb(232,232,232)",
3945
+ "linecolor": "rgb(36,36,36)",
3946
+ "showgrid": false,
3947
+ "showline": true,
3948
+ "ticks": "outside",
3949
+ "title": {
3950
+ "standoff": 15
3951
+ },
3952
+ "zeroline": false,
3953
+ "zerolinecolor": "rgb(36,36,36)"
3954
+ }
3955
+ }
3956
+ },
3957
+ "title": {
3958
+ "text": "Airline Passengers",
3959
+ "x": 0.5
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+ },
3961
+ "width": 650,
3962
+ "xaxis": {
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+ "anchor": "y",
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+ "domain": [
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+ 0,
3966
+ 1
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+ ],
3968
+ "title": {
3969
+ "text": "Date"
3970
+ }
3971
+ },
3972
+ "yaxis": {
3973
+ "anchor": "x",
3974
+ "domain": [
3975
+ 0,
3976
+ 1
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+ ],
3978
+ "title": {
3979
+ "text": "Passengers<br>Box-Cox Transform"
3980
+ }
3981
+ }
3982
+ }
3983
+ }
3984
+ },
3985
+ "metadata": {},
3986
+ "output_type": "display_data"
3987
+ }
3988
+ ],
3989
+ "source": [
3990
+ "plotting(\n",
3991
+ " title=\"Airline Passengers\",\n",
3992
+ " data=data,\n",
3993
+ " x=\"Month\",\n",
3994
+ " y=\"Passengers_box_cox\",\n",
3995
+ " x_label=\"Date\",\n",
3996
+ " y_label=\"Passengers<br>Box-Cox Transform\",\n",
3997
+ " text=True,\n",
3998
+ " lam=lam,\n",
3999
+ ")"
4000
+ ]
4001
+ },
4002
+ {
4003
+ "cell_type": "code",
4004
+ "execution_count": null,
4005
+ "metadata": {},
4006
+ "outputs": [],
4007
+ "source": []
4008
  }
4009
  ],
4010
  "metadata": {