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"source": [
"# Standard data science libraries\n",
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"import plotly.plotly as py\n",
"import plotly.graph_objs as go\n",
"\n",
"import cufflinks\n",
"cufflinks.go_offline()\n",
"\n",
"# Options for pandas\n",
"pd.options.display.max_columns = 20\n",
"\n",
"# Display all cell outputs\n",
"from IPython.core.interactiveshell import InteractiveShell\n",
"InteractiveShell.ast_node_interactivity = 'all'\n"
]
},
{
"cell_type": "code",
"execution_count": 23,
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"end_time": "2018-12-24T22:08:31.320898Z",
"start_time": "2018-12-24T22:08:31.316561Z"
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"source": [
"pmi = pd.DataFrame({'Fund': ['Vanguard Institutional', 'Fidelity 500', 'American Funds'],\n",
" 'Value': ['$1,273,473,951', '$933,104,732', '$127,202,400']})\n",
"\n",
"agi = pd.DataFrame({'Fund': ['Vanguard Institutional', 'Fidelity 500'],\n",
" 'Value': ['$978,581,386', '$835,683,676']})"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-24T22:09:36.535833Z",
"start_time": "2018-12-24T22:09:36.444719Z"
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"title": "Mutual Fund Holdings in Philip Morris",
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"source": [
"pmi.iplot(kind='bar', x='Fund', y='Value',\n",
" layout = dict( margin=dict(l=120), title = 'Mutual Fund Holdings in Philip Morris',\n",
" xaxis = dict(title='Fund', titlefont=dict(size=16)),\n",
" yaxis = dict(title='Value of Holdings', \n",
" titlefont=dict(size=16),\n",
" tickformat=f'$,')))"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-24T22:25:50.061706Z",
"start_time": "2018-12-24T22:25:49.972014Z"
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"layout": {
"margin": {
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"source": [
"agi.iplot(kind='bar', x='Fund', y='Value',\n",
" layout = dict( margin=dict(l=120), title = 'Mutual Fund Holdings in Altria Group',\n",
" xaxis = dict(title='Fund', titlefont=dict(size=16)),\n",
" yaxis = dict(title='Value of Holdings', \n",
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{
"cell_type": "code",
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"metadata": {},
"outputs": [],
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],
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