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slides reborn
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chengjun committed May 6, 2018
1 parent 39f4bd0 commit d878fff
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Showing 76 changed files with 38,697 additions and 53,270 deletions.
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3,001 changes: 2,581 additions & 420 deletions code/12.topic_models.ipynb

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3,498 changes: 0 additions & 3,498 deletions code/12.topic_models_update.ipynb

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28 changes: 14 additions & 14 deletions code/19.visualization_with_pyecharts.ipynb
Expand Up @@ -146315,13 +146315,27 @@
"grid"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Save html files"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-06T07:08:02.417679Z",
"start_time": "2018-05-06T07:08:02.406827Z"
},
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [],
Expand Down Expand Up @@ -149009,20 +149023,6 @@
"tr"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-06T07:06:30.124454Z",
"start_time": "2018-05-06T07:06:30.115445Z"
}
},
"outputs": [],
"source": [
"tr.render()\n"
]
},
{
"cell_type": "code",
"execution_count": 163,
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110 changes: 10 additions & 100 deletions code/19.visualization_with_seaborn.ipynb
Expand Up @@ -265,103 +265,6 @@
"source": [
"ax = sns.barplot(x=\"day\", y=\"total_bill\", hue=\"sex\", data=tips)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"https://github.com/yufeiminds/echarts-python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"pip install echarts-python"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2017-05-17T22:27:55.448906",
"start_time": "2017-05-17T22:27:55.440705"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<echarts.Echart at 0x10750a750>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from echarts import Echart, Legend, Bar, Axis, Line\n",
"from IPython.display import HTML\n",
"\n",
"chart = Echart('GDP', 'This is a fake chart')\n",
"chart.use(Bar('China', [2, 3, 4, 5]))\n",
"chart.use(Legend(['GDP']))\n",
"chart.use(Axis('category', 'bottom', data=['Nov', 'Dec', 'Jan', 'Feb']))\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2017-05-17T22:28:33.014709",
"start_time": "2017-05-17T22:28:33.007739"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<echarts.Echart at 0x10750a890>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chart = Echart('GDP', 'This is a fake chart')\n",
"chart.use(Line('China', [2, 5, 4, 7]))\n",
"chart.use(Legend(['GDP']))\n",
"chart.use(Axis('category', 'bottom', data=['Nov', 'Dec', 'Jan', 'Feb']))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2017-05-17T22:28:34.017149",
"start_time": "2017-05-17T22:28:33.934223"
},
"collapsed": true
},
"outputs": [],
"source": [
"chart.plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -380,7 +283,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
"version": "3.5.4"
},
"latex_envs": {
"bibliofile": "biblio.bib",
Expand All @@ -390,9 +293,16 @@
"eqNumInitial": 0
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_number_sections": true,
"toc_threshold": 6,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
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6 changes: 0 additions & 6 deletions code/Untitled.ipynb

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73 changes: 0 additions & 73 deletions code/first_jupyter_notebook.ipynb

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9 changes: 0 additions & 9 deletions code/items/dir_archive.ini

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38 changes: 0 additions & 38 deletions code/items/m_271af04c30bdbfbb.sidx

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