Removed output from notebooks
This commit is contained in:
katrinamsft
Родитель
4b7726b3f9
Коммит
b8919c2078
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@ -2,49 +2,9 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index(), IPython.notebook.get_selected_index()+1)"
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
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},
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"execution_count": null,
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"<script>\n",
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" code_show=true; \n",
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" function code_toggle() {\n",
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" if (code_show){\n",
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" $('div.input').hide();\n",
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" } else {\n",
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" $('div.input').show();\n",
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" }\n",
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" code_show = !code_show\n",
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" } \n",
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" $( document ).ready(code_toggle);\n",
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" </script>\n",
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" The raw code for this IPython notebook is by default hidden for easier reading toggle on/off the raw code by clicking <a href=\"javascript:code_toggle()\">here</a>."
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"# Copyright (c) Microsoft Corporation.\n",
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"# Licensed under the MIT license.\n",
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@ -101,82 +61,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/markdown": [
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"# Workspace Collaboration Optimizer"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"If your team or company is moving to a new worksite or you need to reorganize an existing workspace, this open-source tool can help. The Workspace Collaboration Optimizer can help you identify and seat teams together in a workspace that maximizes and fosters cross-team productivity and collaboration. You can use this tool to generate floor plans quickly and objectively, in a data-driven way that optimizes employee collaboration by seating teams together. This tool works best in Chrome. "
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"## Distance Helper"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"This notebook produces a distance.csv file, one of the required input files to generate a seating plan. Before running this notebook, make sure you have your zone coordinates to reference and the list of workspaces for your campus. "
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"You can skip this step and move to the Validations notebook if you have already prepared a distance.csv file. You can also skip this step if you only have one building containing all of your workspaces and want to manually create your distance file - See documentation for more details."
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, IPython.notebook.get_selected_index()+2)"
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"display(Markdown(\"# Workspace Collaboration Optimizer\"))\n",
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"display(Markdown(\"If your team or company is moving to a new worksite or you need to reorganize an existing workspace, this open-source tool can help. The Workspace Collaboration Optimizer can help you identify and seat teams together in a workspace that maximizes and fosters cross-team productivity and collaboration. You can use this tool to generate floor plans quickly and objectively, in a data-driven way that optimizes employee collaboration by seating teams together. This tool works best in Chrome. \"))\n",
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@ -189,52 +76,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/markdown": [
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"#### <font color='Green'> 1. Enter the total number of buildings you would like to include in your seating plan. </font>"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"execution_count": null,
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "3f178308e2e749a2be733ac0e1051181",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Text(value='', description='Number of buildings', style=DescriptionStyle(description_width='185px'))"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "4a85b7b96c5b471bbfc92aaa5194946f",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Button(button_style='primary', description='Go', style=ButtonStyle())"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"style = {'description_width': '185px'}\n",
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"layout = {'width': '365px'}\n",
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@ -254,9 +98,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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@ -291,9 +133,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"import time\n",
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@ -360,9 +200,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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" #now add these columns to dataframe \n",
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@ -380,9 +218,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"columnsFLR = ['Number of Floors']\n",
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@ -458,9 +294,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"#### clear_output()\n",
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@ -483,9 +317,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"#dffloorsFINAL = to_dataframe(sheetnameFLRS)\n",
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@ -518,9 +350,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"display(Markdown(\"#### <font color='Green'> 7. Enter a unique workspace name for each zone. </font>\"))\n",
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@ -544,9 +374,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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@ -2,59 +2,9 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index(), IPython.notebook.get_selected_index()+1)"
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index(), IPython.notebook.get_selected_index()+1)"
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"<script>\n",
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" code_show=true; \n",
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" function code_toggle() {\n",
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" if (code_show){\n",
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" $('div.input').hide();\n",
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" } else {\n",
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" $('div.input').show();\n",
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" }\n",
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" code_show = !code_show\n",
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" } \n",
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" $( document ).ready(code_toggle);\n",
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" </script>\n",
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" The raw code for this IPython notebook is by default hidden for easier reading toggle on/off the raw code by clicking <a href=\"javascript:code_toggle()\">here</a>."
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"# Copyright (c) Microsoft Corporation.\n",
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"# Licensed under the MIT license.\n",
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@ -89,24 +39,9 @@
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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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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "e42584f829d14aeebf29c98e35fd2f01",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(Output(), ToggleButtons(button_style='info', options=('Standard',), value=None)))"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"import pandas as pd \n",
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"import numpy as np\n",
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@ -190,100 +125,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, IPython.notebook.get_selected_index()+2)"
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"## Standard"
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],
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"text/plain": [
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"<IPython.core.display.Markdown object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
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"<b>All four files will be programmatically read from previous stage of validations from the Final Files set folder:</b> "
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],
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"text/plain": [
|
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"<IPython.core.display.Markdown object>"
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]
|
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/markdown": [
|
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"{interactions.csv, team_size.csv, space_capacity.csv, and distance.csv}"
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],
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"text/plain": [
|
||||
"<IPython.core.display.Markdown object>"
|
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]
|
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "11ffd0ac244e4b289289d56c5fd6b736",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
|
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"Output(layout=Layout(border='1px solid black'))"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
|
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"application/vnd.jupyter.widget-view+json": {
|
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"model_id": "f939a87c90e84c2987d63d1d03f1dbfa",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Output()"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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||||
"application/vnd.jupyter.widget-view+json": {
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||||
"model_id": "7b94eb9b868449a38af10ef262f3a6d4",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"HBox(children=(Text(value='', description='New results name:', layout=Layout(width='385px'), placeholder='No.x…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"def go_to_nextblock(btn):\n",
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" display(Javascript('IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, IPython.notebook.get_selected_index()+3)'))\n",
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@ -971,44 +815,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
|
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"name": "stdout",
|
||||
"output_type": "stream",
|
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"text": [
|
||||
"You did not enter an output file name above. A default name of [floor_plan_2021-06-22T100726 ] will be used.\n",
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"\u001b[1m floor_plan_2021-06-22T100726.xlsx\n"
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]
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},
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{
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||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "11ffd0ac244e4b289289d56c5fd6b736",
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||||
"version_major": 2,
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||||
"version_minor": 0
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},
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"text/plain": [
|
||||
"Output(layout=Layout(border='1px solid black'))"
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]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"application/javascript": [
|
||||
"IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, IPython.notebook.get_selected_index()+1)"
|
||||
],
|
||||
"text/plain": [
|
||||
"<IPython.core.display.Javascript object>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"clear_output()\n",
|
||||
"global out_filename\n",
|
||||
|
|
|
|||
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