bacterial_bioreactor.ipynb

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    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# find and open file as pandas dataframe\n",
    "df = pd.read_csv('bioreactor.csv') \n",
    "\n",
    "#sort by abundance\n",
    "df = df.query('t19 > 100')\n",
    "OTU_ID = list(df['OTU_ID'])\n",
    "\n",
    "# shorten names\n",
    "shorter_OTU_ID = []\n",
    "for string in OTU_ID:\n",
    "    start_pos = string.find('g__')\n",
    "    end_pos = string.find(';s__')\n",
    "    shorter_OTU_ID.append(string[start_pos:end_pos])\n",
    "\n",
    "# making dataframe and list2 of days \n",
    "col_names = list(df.columns)\n",
    "data_per_date = []\n",
    "for col_name in col_names[1:]:\n",
    "  data_per_date.append(df[col_name])\n",
    "\n",
    "# generating heatmap\n",
    "trace = go.Heatmap(z = data_per_date,\\\n",
    "                   x = shorter_OTU_ID,\\\n",
    "                   y = col_names[1:])\n",
    "data = [trace]\n",
    "layout = go.Layout(title = 'Bioreactor Timecourse OTU Heatmap',\\\n",
    "                   xaxis = dict(title = 'Bacterial Genus'),\\\n",
    "                    yaxis = dict(title = 'Day of Sample Collection'),\\\n",
    "                    margin = go.Margin(\n",
    "                            b=125))\n",
    "figure = go.Figure(data=data, layout=layout)\n",
    "py.iplot(figure)\n",
    "\n",
    "\n"
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