02_dstemplate2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Adapted for use with nbdev & Google Colab from [xstreamsrl Jupytemplate](https://github.com/donlelef/jupytemplate). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#default_exp dstemplate2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "#test_flag_colab\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "try:\n",
    "  import nbdev\n",
    "except:\n",
    "  !pip install nbdev\n",
    "  !pip install fastcore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "# %cd /content/drive/My Drive/<project directory>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "# not deps but we need them to use nbdev and run tests\n",
    "from nbdev import * \n",
    "from nbdev.showdoc import *\n",
    "from fastcore.test import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DSTemplate2\n",
    "\n",
    "> A standard yet flexible skeleton for every kind of Data Science notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## \n",
    "\n",
    "**Title**\n",
    "\n",
    "*The title of the notebook (above) should be coherent with file name (at the top)  and, like the filename, follow the nbdev naming convention. For example, notebook '01' to be added to the project by author 'AB' (initials) and containing code for 'data_exploration' might have the filename `01_AB_data_exploration.ipynb` or `AB_01_data_exploration.ipynb` and title '01_AB_Data_Exploration' or 'AB_01_Data_Exploration'.*\n",
    "\n",
    "*Note that this title will also become the title of the notebook in the documentation.*\n",
    "\n",
    "**Purpose**\n",
    "\n",
    "*State the purpose of the notebook.*\n",
    "\n",
    "**Methodology**\n",
    "\n",
    "*Quickly describe assumptions and processing steps.*\n",
    "\n",
    "**WIP - improvements**\n",
    "\n",
    "*Use this section only if the notebook is not final.*\n",
    "\n",
    "**Notable TODOs:**\n",
    "\n",
    "*todo 1;*\n",
    "*todo 2;*\n",
    "*todo 3*. \n",
    "\n",
    "**Results**\n",
    "\n",
    "*Describe and comment the most important results.*\n",
    "\n",
    "**Suggested next steps**\n",
    "\n",
    "*State suggested next steps, based on results obtained in this notebook*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "Import all the required **Python** libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
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     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
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   "source": [
    "#test_flag_deps\n",
    "\n",
    "# general\n",
    "import os, pickle, pathlib\n",
    "\n",
    "# Data manipulation\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Options for pandas\n",
    "pd.options.display.max_columns = 50\n",
    "pd.options.display.max_rows = 30\n",
    "\n",
    "# Visualizations\n",
    "import matplotlib as plt\n",
    "\n",
    "import plotly\n",
    "import plotly.graph_objs as go\n",
    "import plotly.offline as ply\n",
    "plotly.offline.init_notebook_mode(connected=True)\n",
    "\n",
    "import altair as alt\n",
    "\n",
    "import cufflinks as cf\n",
    "cf.go_offline(connected=True)\n",
    "cf.set_config_file(theme='white')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Import all required **local** libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Include local library paths\n",
    "import sys\n",
    "# sys.path.append('path/to/local/lib') # put path to local libraries in system path\n",
    "# Import local libraries # now local libraries in a non_local directory ('lib') can be easily imported\n",
    "\n",
    "from nbds_colab.common import *\n",
    "from nbds_colab.vis import *\n",
    "from nbds_colab.dataproc import *\n",
    "from nbds_colab.data import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameter definition\n",
    "Set all relevant parameters for our notebook. By convention, parameters are uppercase, while all the \n",
    "other variables follow Python's guidelines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "PARAM = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data import\n",
    "Retrieve required data for analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data processing\n",
    "Put here the core of the notebook. Feel free to further split this section into subsections and adjust heading markdown as fits the project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#export\n",
    "def template2_test(test_msg):\n",
    "  \"Function template2\"\n",
    "  return test_msg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'template2'"
      ]
     },
     "execution_count": null,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "template2_test('template2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test local imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert common_test('from common') == 'from common'\n",
    "assert vis_test('from vis') == 'from vis'\n",
    "assert dataproc_test('from dataproc') == 'from dataproc'\n",
    "assert data_test('from data') == 'from data'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "Relevant references:\n",
    "1. author1, article1, journal1, year1, url1\n",
    "2. author2, article2, journal2, year2, url2"
   ]
  }
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