bioplastic/Locally produced PLA filament survey.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Background\n",
    "\n",
    "A survey was done to evaluate whether it was commercial interest in Norway for PLA 3d-printer filament that is locally produced. And whether people were interested in returning failed prints and other sources of PLA waste for recycling.\n",
    "\n",
    "The motivation for the survey is a long-term goal of establishing a financially sustainable circular lifecycle for PLA bioplastic.\n",
    "\n",
    "The survey was posted to two Norwegian Facebook groups focused on 3d-printing and 'making' on a Saturday in Feburary, 2018. Each group had approximately 1500 members. 120 reponses were collected over 2 weeks, approx 4% of the total 3000 group members (many which may not actually be active).\n",
    "\n",
    "### Authors\n",
    "Jon Nordby, <jononor@gmail.com>, https://github.com/jonnor/, [@jononor](http://twitter.com/jononor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas\n",
    "import numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Raw data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Responses: 121\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Hvor mange 3d-printere har du i aktiv bruk i dag?</th>\n",
       "      <th>Hvor mange kilo PLA filament kjøper du per år?</th>\n",
       "      <th>Hvilken diameter bruker du (mest)?</th>\n",
       "      <th>Hva er det meste du er villig til å betale for norskprodusert PLA filament?</th>\n",
       "      <th>Hvilke farger bruker du mest? (maks 3 valg)</th>\n",
       "      <th>Hvor mye PLA filament kan du levere til gjenvinning per år?</th>\n",
       "      <th>Vil du høre mer via epost når vi lanserer?</th>\n",
       "      <th>Har du noen tilbakemeldinger eller tips til oss?</th>\n",
       "      <th>Hvor i Norge bor du?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/17/2018 15:34:51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1.75 mm</td>\n",
       "      <td>mindre enn 300 kr/kg</td>\n",
       "      <td>Sort, Hvit, Klar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nei</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/17/2018 16:20:34</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>1.75 mm</td>\n",
       "      <td>350 kr / kg</td>\n",
       "      <td>Sort, Hvit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Timestamp  Hvor mange 3d-printere har du i aktiv bruk i dag?  \\\n",
       "0  2/17/2018 15:34:51                                                NaN   \n",
       "1  2/17/2018 16:20:34                                                2.0   \n",
       "\n",
       "   Hvor mange kilo PLA filament kjøper du per år?  \\\n",
       "0                                               0   \n",
       "1                                              10   \n",
       "\n",
       "  Hvilken diameter bruker du (mest)?  \\\n",
       "0                            1.75 mm   \n",
       "1                            1.75 mm   \n",
       "\n",
       "  Hva er det meste du er villig til å betale for norskprodusert PLA filament?  \\\n",
       "0                               mindre enn 300 kr/kg                            \n",
       "1                                        350 kr / kg                            \n",
       "\n",
       "  Hvilke farger bruker du mest? (maks 3 valg)  \\\n",
       "0                            Sort, Hvit, Klar   \n",
       "1                                  Sort, Hvit   \n",
       "\n",
       "   Hvor mye PLA filament kan du levere til gjenvinning per år?  \\\n",
       "0                                                NaN             \n",
       "1                                                2.0             \n",
       "\n",
       "   Vil du høre mer via epost når vi lanserer?  \\\n",
       "0                                         NaN   \n",
       "1                                         NaN   \n",
       "\n",
       "  Har du noen tilbakemeldinger eller tips til oss? Hvor i Norge bor du?  \n",
       "0                                              Nei                  NaN  \n",
       "1                                              NaN                  NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw = pandas.read_csv('./data/plafab-oslo-survey.anonymized.csv')\n",
    "print('Responses:', len(raw))\n",
    "raw[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>printers</th>\n",
       "      <th>filament purchased</th>\n",
       "      <th>diameter used</th>\n",
       "      <th>price preference</th>\n",
       "      <th>colors used</th>\n",
       "      <th>filament for recycling</th>\n",
       "      <th>contact_email</th>\n",
       "      <th>feedback</th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/17/2018 16:20:34</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>1.75 mm</td>\n",
       "      <td>350 kr / kg</td>\n",
       "      <td>Sort, Hvit</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2/17/2018 16:21:15</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.75 mm</td>\n",
       "      <td>400 kr / kg</td>\n",
       "      <td>Hvit, Grå, Grønn</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "            timestamp  printers  filament purchased diameter used  \\\n",
       "1  2/17/2018 16:20:34       2.0                  10       1.75 mm   \n",
       "2  2/17/2018 16:21:15       1.0                   3       1.75 mm   \n",
       "\n",
       "  price preference       colors used  filament for recycling  contact_email  \\\n",
       "1      350 kr / kg        Sort, Hvit                     2.0            NaN   \n",
       "2      400 kr / kg  Hvit, Grå, Grønn                     2.0            NaN   \n",
       "\n",
       "  feedback location  \n",
       "1      NaN      NaN  \n",
       "2      NaN      NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "field_name_map = {\n",
    "    'Hvor mange 3d-printere har du i aktiv bruk i dag?': 'printers', # currently active\n",
    "    'Hvor mange kilo PLA filament kjøper du per år?': 'filament purchased', # per year\n",
    "    'Hvilken diameter bruker du (mest)?': 'diameter used',\n",
    "    'Hva er det meste du er villig til å betale for norskprodusert PLA filament?': 'price preference',\n",
    "    'Hvilke farger bruker du mest? (maks 3 valg)': 'colors used',\n",
    "    'Hvor mye PLA filament kan du levere til gjenvinning per år?': 'filament for recycling', # i kilos\n",
    "    'Vil du høre mer via epost når vi lanserer?': 'contact_email',\n",
    "    'Har du noen tilbakemeldinger eller tips til oss?': 'feedback',\n",
    "    'Hvor i Norge bor du?': 'location',\n",
    "    'Timestamp': 'timestamp',\n",
    "}\n",
    "cleaned = raw.rename(columns=field_name_map)\n",
    "cleaned.drop(0, inplace=True) # submission test\n",
    "cleaned[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>colors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>black</th>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blue</th>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gray</th>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>green</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orange</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>red</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>transparent</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>white</th>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             colors\n",
       "black            91\n",
       "blue             31\n",
       "gray             48\n",
       "green             8\n",
       "orange            4\n",
       "other             4\n",
       "red              28\n",
       "transparent       2\n",
       "white            82"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_name_map = {\n",
    "    'sort': 'black',\n",
    "    'hvit': 'white',\n",
    "    'grå': 'gray',\n",
    "    'grønn': 'green',\n",
    "    'rød': 'red',\n",
    "    'blå': 'blue',\n",
    "    'klar': 'transparent',\n",
    "    'transparent': 'transparent',\n",
    "    'oransje': 'orange',\n",
    "    'oransj': 'orange',\n",
    "    'orange': 'orange',\n",
    "}\n",
    "colors = {}\n",
    "for row in cleaned['colors used']:\n",
    "    used = row.split(',')\n",
    "    for c in used:\n",
    "        original = c.strip().lower()\n",
    "        mapped = color_name_map.get(original, \"other\")\n",
    "        #if mapped == 'other': print('unknown color:', original)\n",
    "        if colors.get(mapped) is None:\n",
    "            colors[mapped] = 0\n",
    "        colors[mapped] += 1\n",
    "colors = pandas.DataFrame({'colors': colors})\n",
    "colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "299 kr/kg or less    39\n",
       "300 kr / kg          38\n",
       "350 kr / kg          26\n",
       "400 kr / kg          12\n",
       "500 kr / kg           3\n",
       "501 kr/kg or more     1\n",
       "450 kr / kg           1\n",
       "Name: price preference, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preference_map = {\n",
    "    'mindre enn 300 kr/kg': '299 kr/kg or less',\n",
    "    'mer enn 500 kr/kg': '501 kr/kg or more',\n",
    "}\n",
    "cleaned['price preference'].replace(preference_map, inplace=True)\n",
    "cleaned['price preference'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1   2018-02-17 16:20:34\n",
       "2   2018-02-17 16:21:15\n",
       "Name: timestamp, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned['timestamp'] = pandas.to_datetime(cleaned['timestamp'])\n",
    "cleaned['timestamp'][:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Responses\n",
    "\n",
    "**50% left their email addresses** for further news/update about the project. This is a pretty strong indicator of interest in the project.\n",
    "\n",
    "Note: Raw data unavailable about who left email is unavailable, email was nulled for anonymization reasons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kKVdZh+G6UpuEZ6GTJEnKU9ZheNfMcKMzw5IkSVkyDGObhCRJUq7yDsO1xeHbJiFJkpSn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\nlMEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2d3c705978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "timed = cleaned.copy()\n",
    "timed.index = timed['timestamp']\n",
    "timed['printers'].resample('3h').count().plot(figsize=(12,6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most responses were made immediately after posting. Over 50 responses of the 120 responses were made within the first 3 hours. This may be partly due to Facebook preference of giving visibility to very recent content.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Printers in use\n",
    "This question was included mostly to ensure that those that respond actually are potential customers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0     6\n",
       "1.0    65\n",
       "2.0    32\n",
       "3.0     9\n",
       "4.0     3\n",
       "5.0     1\n",
       "6.0     4\n",
       "Name: printers, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kk939qe7+UpJ3JLl6d8YCAID1q+4+uxdWvSLJVd396tXj70zyTd39mkfsdyzJsdXD5yT5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\nAMYSwwAAjCWGAQAY6/8BzZ68KWAMnXIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2d3a6df630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "printer_count = cleaned['printers'].value_counts().sort_index()\n",
    "printer_count.plot(kind='bar', figsize=(12,6))\n",
    "printer_count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Majority of respondents have 1 printer in use. However over 40% have more than one."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filament purchase\n",
    "\n",
    "Per year\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JdPdVSc5J8oAkB1bV/vOiw5NctoNtTuruo7r7qE2bNt2QWgEAYF2t5W4Sm6rqwPnxtyR5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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2d3a4c22e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filament_purchase_counts = cleaned['filament purchased'].value_counts().sort_index()\n",
    "filament_purchase_counts.plot(kind='bar', figsize=(12, 6), title='Filament purchased (kg per year)')\n",
    "filament_purchase_counts.median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A large amount of respondents say they buy more than 10kg/year, and the median is 7 kg/year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "785"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned['filament purchased'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just by providing these 120 respondends with *parts* of their consumption can cover 100++ kg/yearly. With targeted marketing in the communities the survey was shared with, it could be possible to sell 1000 kg/yearly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filament for recycling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+zRmuqpOS3C/JBfOiJ1fVxVX1nKo6Zi+POaOqLqyqC3fu3LmuYgEAYCOtOQxX1W2S/GWS\np3T3Z5L8UZK7JdmeaeT4d/b0uO4+u7t3dPeObdu2bUDJAACwMdYUhqvq5pmC8Au6+2VJ0t1XdfeN\n3f3FJM9OcvLmlQkAABtvLWeTqCTnJLmsu393xfLjVzT73iSXbnx5AACwedZyNokHJ3lskkuq6qJ5\n2S8keUxVbU/SSS5P8sRNqRAAADbJWs4m8eYktYdVr9r4cgAAYOu4Ah0AAMMShgEAGJYwDADAsIRh\nAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDEoYBABiWMAwAwLCEYQAAhiUMAwAwLGEYAIBh\nCcMAAAxLGAYAYFjCMAAAwxKGAQAYljAMAMCwhGEAAIYlDAMAMCxhGACAYQnDAAAMSxgGAGBYwjAA\nAMMShgEAGJYwDADAsIRhAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDEoYBABiWMAwAwLCE\nYQAAhiUMAwAwrFXDcFXdpapeX1WXVdV7quqn5+W3q6rXVNX75u/HbH65AACwcdYyMnxDkp/p7nsl\neWCSJ1XVvZOcmeS13X33JK+d7wMAwCFj1TDc3Vd29zvn29cluSzJnZM8Ksm5c7Nzk5y2WUUCAMBm\nOHJ/GlfVSUnul+SCJMd195XJFJir6g57ecwZSc5IkhNPPHE9tSZJTjrzb9a9jfW6/BnftewSAADY\nAGs+gK6qbpPkL5M8pbs/s9bHdffZ3b2ju3ds27btQGoEAIBNsaYwXFU3zxSEX9DdL5sXX1VVx8/r\nj09y9eaUCAAAm2MtZ5OoJOckuay7f3fFqvOSnD7fPj3JKza+PAAA2DxrmTP84CSPTXJJVV00L/uF\nJM9I8pKqenySjyT5gc0pEQAANseqYbi735yk9rL6YRtbDgAAbB1XoAMAYFjCMAAAwxKGAQAYljAM\nAMCwhGEAAIYlDAMAMCxhGACAYQnDAAAMSxgGAGBYwjAAAMMShgEAGJYwDADAsIRhAACGJQwDADAs\nYRgAgGEJwwAADEsYBgBgWMIwAADDEoYBABiWMAwAwLCEYQAAhiUMAwAwLGEYAIBhCcMAAAxLGAYA\nYFjCMAAAwxKGAQAYljAMAMCwhGEAAIYlDAMAMKwjl10AsLEuu+e9ll1C7vXey5ZdAgCsiZFhAACG\nJQwDADAsYRgAgGEJwwAADEsYBgBgWKuG4ap6TlVdXVWXrlh2VlV9rKoumr++c3PLBACAjbeWkeHn\nJTllD8uf2d3b569XbWxZAACw+VYNw939piSf2oJaAABgS61nzvCTq+rieRrFMRtWEQAAbJEDDcN/\nlORuSbYnuTLJ7+ytYVWdUVUXVtWFO3fuPMDdAQDAxjugMNzdV3X3jd39xSTPTnLyPtqe3d07unvH\ntm3bDrROAADYcAcUhqvq+BV3vzfJpXtrCwAAB6sjV2tQVS9M8pAkx1bVFUmemuQhVbU9SSe5PMkT\nN7FGAADYFKuG4e5+zB4Wn7MJtQAAwJZyBToAAIYlDAMAMCxhGACAYQnDAAAMSxgGAGBYwjAAAMMS\nhgEAGJYwDADAsIRhAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDEoYBABiWMAwAwLCEYQAA\nhiUMAwAwLGEYAIBhCcMAAAxLGAYAYFjCMAAAwxKGAQAYljAMAMCwhGEAAIYlDAMAMCxhGACAYQnD\nAAAMSxgGAGBYwjAAAMMShgEAGJYwDADAsIRhAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWKuG4ap6\nTlVdXVWXrlh2u6p6TVW9b/5+zOaWCQAAG28tI8PPS3LKbsvOTPLa7r57ktfO9wEA4JCyahju7jcl\n+dRuix+V5Nz59rlJTtvgugAAYNMd6Jzh47r7yiSZv99hbw2r6oyqurCqLty5c+cB7g4AADbeph9A\n191nd/eO7t6xbdu2zd4dAACs2YGG4auq6vgkmb9fvXElAQDA1jjQMHxektPn26cnecXGlAMAAFtn\nLadWe2GStyb5uqq6oqoen+QZSR5RVe9L8oj5PgAAHFKOXK1Bdz9mL6setsG1AADAlnIFOgAAhiUM\nAwAwLGEYAIBhCcMAAAxLGAYAYFjCMAAAwxKGAQAYljAMAMCwhGEAAIYlDAMAMCxhGACAYQnDAAAM\nSxgGAGBYwjAAAMMShgEAGJYwDADAsIRhAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDEoYB\nABiWMAwAwLCEYQAAhiUMAwAwLGEYAIBhCcMAAAxLGAYAYFjCMAAAwxKGAQAY1pHLLgAAgIPDHV9/\n0bJLSJJ84tu2b9m+jAwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDWtfZJKrq8iTXJbkxyQ3dvWMj\nigIAgK2wEadW+7bu/uQGbAcAALaUaRIAAAxrvSPDneT8quokz+rus3dvUFVnJDkjSU488cR17g5g\n7f7gJ1+37BLypD9+6LJLAGAf1jsy/ODuvn+SU5M8qaq+ZfcG3X12d+/o7h3btm1b5+4AAGDjrCsM\nd/fH5+9XJ3l5kpM3oigAANgKBxyGq+orq+qoXbeTfHuSSzeqMAAA2GzrmTN8XJKXV9Wu7fx5d//t\nhlQFAABb4IDDcHd/MMl9N7AWAADYUk6tBgDAsIRhAACGJQwDADCsjbgcMwAHsd/5we9edglJkp95\n8SuXXQLAlzEyDADAsIRhAACGJQwDADAsYRgAgGEJwwAADEsYBgBgWMIwAADDEoYBABiWMAwAwLCE\nYQAAhiUMAwAwLGEYAIBhCcMAAAxLGAYAYFjCMAAAwxKGAQAYljAMAMCwhGEAAIYlDAMAMCxhGACA\nYQnDAAAMSxgGAGBYwjAAAMMShgEAGJYwDADAsIRhAACGJQwDADCsI5ddAABslSvO/Idll5AkOeEZ\n/2XZJeSss85adglJDo46Xvu6uy27hCTJwx76gWWXMCQjwwAADEsYBgBgWMIwAADDEoYBABjWusJw\nVZ1SVf9SVe+vqjM3qigAANgKBxyGq+qIJH+Q5NQk907ymKq690YVBgAAm209I8MnJ3l/d3+wu/89\nyYuSPGpjygIAgM23njB85yQfXXH/inkZAAAcEqq7D+yBVT+Q5Du6+wnz/ccmObm7/+du7c5IcsZ8\n9+uS/MuBl7shjk3yySXXcLDQFwv6YkFfLOiLBX2xoC8W9MWCvlg4WPrirt29bbVG67kC3RVJ7rLi\n/glJPr57o+4+O8nZ69jPhqqqC7t7x7LrOBjoiwV9saAvFvTFgr5Y0BcL+mJBXywcan2xnmkSb09y\n96r66qq6RZJHJzlvY8oCAIDNd8Ajw919Q1U9OcnfJTkiyXO6+z0bVhkAAGyy9UyTSHe/KsmrNqiW\nrXLQTNk4COiLBX2xoC8W9MWCvljQFwv6YkFfLBxSfXHAB9ABAMChzuWYAQAYljAMAMCwhGEAAIa1\nrgPoDiVVdbsk3d3XLLsWDg5VdVymqyZ2ko9391VLLmmpvEcW9MXEe2RBXyzoi5vyeXHoO6wPoKuq\nE5P8VpKHJbk2SSX5qiSvS3Jmd1++vOqWZ/QPsqranuSPk9w2ycfmxSdkeo38j+5+57Jq22reIwv6\nYsF7ZEFfLOiLBZ8XN1VVt01ySlZkiyR/193XLrWwNTrcw/Bbk/zvJH/R3TfOy45I8gNJntLdD1xm\nfVvNB9mkqi5K8sTuvmC35Q9M8qzuvu9yKtt63iML+mLBe2RBXyzoiwWfFwtV9aNJnprk/Nw0Wzwi\nydO6+0+XVdtaHe5h+H3dfff9XXe48kE2WeV18f7u/tqtrmlZvEcW9MWC98iCvljQFws+Lxaq6l+S\nPGD3UeCqOibJBd19j+VUtnaH+5zhd1TVHyY5N8lH52V3SXJ6knctrarl+crdg3CSdPc/VdVXLqOg\nJXl1Vf1Nkj/NTV8XP5rkb5dW1XJ4jyzoiwXvkQV9saAvFnxeLFSmqRG7++K87qB3uI8M3yLJ45M8\nKtM8lsr0ov3rJOd09xeWWN6Wq6rfT3K37PmD7EPd/eRl1bbVqurU3PR1cUWS8+arKg7De2RBX9yU\n98iCvljQFxOfFwtVdXqSX8k0TWJXtjgx0zSJX+3u5y2ptDU7rMMwX84HGQCwkeYpEd+Rm2aLvztU\nzrAxbBiuqu/u7lcuuw4OLlV1RncfUtdU3yzeIwv6YsF7ZEFfLOiLBZ8Xh56RL7rxTcsu4GBSVWcs\nu4aDxCExv2mLeI8s6IsF75EFfbGgLxZ8Xsyq6pD4A+mwHxmuqntmMS1g17nvzuvuy5Za2EGmqp7Y\n3c9adh1bZX5d3DnTka7Xr1h+SncPdSBIVZ2c6YTxb6+qe2c6V+R7TZ1JqupPu/tHl13HslXVNyc5\nOcml3X3+suvZSlX1gCSXdfdnqupWSc5Mcv8k/5zk17v700stcAtV1U8leXl3f3TVxoe5ec7wozOd\nq//vq+qHkvznJJclObu7/2OpBR4kquobu/sdy65jNYd1GK6qn0vymCQvyjR/JZnOfffoJC/q7mcs\nq7aDTVU9rrufu+w6tsL8gf6kTB9a25P8dHe/Yl73zu6+/zLr20pV9dQkp2Y6s8xrkjwgyRuSPDzT\nfK9fW151W6uqztt9UZJvy3QS/XT392x5UUtSVW/r7pPn2z+R6f3y8iTfnuSvR/rsrKr3JLlvd98w\nj3J9LslfZLrYwn27+78utcAtVFWfTvLZJB9I8sIkL+3uncutajmq6gWZPjdvnelc/bdJ8rJMr4t0\n948trTj22+Eehv81ydfv/hfa/Bfde0Y6D+Bqquoj3X3isuvYClV1SZIHdff1VXVSpl9sz+/u36uq\nd3X3/ZZa4Baa+2J7klsm+USSE1aMgF3Q3d+w1AK3UFW9M9No359k+i9SZfqF/+gk6e43Lq+6rbXy\nfVBVb0/ynd29cz4F4z91932WW+HWqarLuvte8+2b/LFcVRd19/blVbe1qupdSb4x0x/LP5jke5K8\nI9P75GXdfd0Sy9tSVXVxd39DVR2Z6UITd+ruG6uqkrx7sM/O2yb5+SSnJdk2L746ySuSPONQuArd\n4T5n+ItJ7rSH5cfP64ZSVRfv5euSJMctu74tdMSuqRHzJTMfkuTUqvrdjDfv7YbuvrG7P5fkA939\nmSTp7s9nvPfIjky/2H8xyae7+w1JPt/dbxwpCM9uVlXHVNXtMw2a7EyS7v5skhuWW9qWu7SqHjff\nfndV7UiSqrpHktH+Fd7d/cXuPr+7H5/p9+sfZppa9cHllrblbjYPrB2VaXT4tvPyWya5+dKqWo6X\nJLkmyUO6+/bdfftM/1W7JslLl1rZGh3uF914SpLXVtX7ctNz331tkmHOqbvCcZlOfbL7qU4qyT9u\nfTlL84mq2t7dFyXJPEL83Umek2SYEa/Zv1fVrecw/I27Fs5/6Q8Vhrv7i0meWVUvnb9flcP/M3Jv\nbpvpD4NK0lV1x+7+RFXdJuP9wfiEJL9XVb+U5JNJ3lpVH830O+UJS61s693kZz//1/W8JOfN/00a\nyTlJ3pvkiEx/QL+0qj6Y5IGZpmaO5KTu/s2VC7r7E0l+s6p+fEk17ZfDeppEklTVzTId+LHy3Hdv\n33Ut8ZFU1TlJntvdb97Duj/v7h9aQllbrqpOyDQi+ok9rHtwd79lCWUtRVXdck8nh6+qY5Mc392X\nLKGsg0JVfVeSB3f3Lyy7loNFVd06yXHd/aFl17LVquqoJF+T6Q+kK7r7qiWXtOWq6h7d/a/LruNg\nUVV3SpLu/nhVHZ1p+shHuvtty61sa1XV+Un+Psm5u94XVXVckh9L8ojufvgSy1uTwz4MAwCwOeYL\nbpyZ6cxdd5gXX5XpvwbPOBQuvCEMAwCw4Q6VM1UJwwAAbLhD5UxVox4cAgDAOlXVxXtblUPkTFXC\nMAAAB+qQP1OVMAwAwIF6ZZLb7Dpd6UpV9YatL2f/mTMMAMCwDvcr0AEAwF4JwwAADEsYBgBgWMIw\nAADDEoYBABjW/wfCuZij5Cr8cwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2d3a3a41d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filament_recycle_counts = cleaned['filament for recycling'].value_counts().sort_index()\n",
    "filament_recycle_counts.plot(kind='bar', figsize=(12, 6), title='Filament for recyling (kg per year)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "265.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned['filament for recycling'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The amount of filament people say they have for recycling is naturally significantly less than what they buy.\n",
    "\n",
    "Nevertheless, for these 120 respondents, the sum is estimated to nearly 300 kg. Assuming 300 NOK/kg for the filament purchase price, that is an economic waste of 80'000 NOK yearly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Color options\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UwDAlSZJUwDAlSZJUwDAlSZJUwL35JEk9Nah7Eg7q8x4EjkxJkiQVMExJkiQVMExJkiQV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\nAoYpSZKkAv8fxIlXhV+d7UsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc4ea7f2470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors.sort_values(by='colors', ascending=False).plot(kind='bar', figsize=(10, 5));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most used are black,white and gray. It looks like one could do OK by offering just 2-3 filament colors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Diameter options\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.75 mm    0.925620\n",
       "2.85 mm    0.066116\n",
       "3.0 mm     0.008264\n",
       "Name: diameter used, dtype: float64"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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G+GHgQGC7zsZKxmKWEhlixkYnLfmnOXsOn8NFYwdeMR55PHUmJdGLN0makFaK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\nliSpRCxmSZJKxGKWJKlE/j91+6OLWOkUMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc4ead0bcf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cleaned['diameter used'].value_counts().plot(kind='pie', figsize=(8,8))\n",
    "cleaned['diameter used'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Over 90% used 1.75 mm filament. It should be OK to only offer this variant."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Price preference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "299 kr/kg or less    0.330579\n",
       "300 kr / kg          0.314050\n",
       "350 kr / kg          0.214876\n",
       "400 kr / kg          0.099174\n",
       "500 kr / kg          0.024793\n",
       "501 kr/kg or more    0.008264\n",
       "450 kr / kg          0.008264\n",
       "Name: price preference, dtype: float64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wFHCpa9Vsn42/v0n+yROnJ+f4TSbJA+mvhKyqjw2dZ0ReA5yf5Gy6TzUOB17V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\nSZIa/H8riSA4bV6AmwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc4eaa62630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price_counts = cleaned['price preference'].value_counts().sort_index()\n",
    "price_counts.plot(kind='bar', figsize=(10,6))\n",
    "cleaned['price preference'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "People have a **very strong preference for cheap filament**, with two thirds choosing the two lowest options.\n",
    "\n",
    "There is **no indication that people are willing to pay more for locally produced filament**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusions\n",
    "\n",
    "The high amount of respondents, and high amount of filament purchased by respondents indicate it is possible to sell an amount of filament needed for a micro business (NNN-NNNN kilos/year).\n",
    "\n",
    "However there is no support for the thesis that consumers are willing to pay a premium for 'locally produced' (filament from raw pellets). This means that without other differentiation, one has to compete on price alone. As prices are likely to drop in the future, this seems a rather weak position. \n",
    "\n",
    "More data would be needed on the production side in order to determine whether there could be sufficient margin to operate. However the prices indicated here suggest a low margin.\n",
    "\n",
    "## Quality concerns\n",
    "\n",
    "The quality of product needed for 3d-printing filament is very high. Tolerances of diameter variation, foreign substances, plastic properties that stay over time (ex: low brittleness).\n",
    "\n",
    "Attempting to recyle material means trying to deliver needed quality from a material stream with many varying  parameters. One also needs to get the material to facilities. Without a price preference, all this must be should be achievable at prices comparable to that of pure PLA material, currently below 50 NOK/kg.\n",
    "\n",
    "So to enable a circular lifecycle with recycled inputs, it would be better to find less quality-critical uses for the plastic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}