01_Build_Podcast_List.ipynb

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   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import guess_language"
   ]
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   "cell_type": "code",
   "execution_count": 50,
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   "source": [
    "# load all .tsv files\n",
    "# source: https://github.com/ageitgey/all-podcasts-dataset\n",
    "colNames = ['slug', 'name', 'image_url', 'feed_url', 'website_url', 'itunes_owner_name', 'itunes_owner_email', 'managing_editor_name', 'managing_editor_email', 'explicit', 'description', 'itunes_summary'] \n",
    "podcastDf = pd.DataFrame(columns=colNames)\n",
    "files = !ls data/*.tsv\n",
    "\n",
    "for file in files:\n",
    "    podcastDf = podcastDf.append(pd.read_table(file, header=None, names=colNames), ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
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   "source": [
    "# remove podcasts that don't have itunes summary or itunes explicit rating (probably not in itunes)\n",
    "# remove podcasts that don't have feed url\n",
    "podcastDf = podcastDf.dropna(subset=['itunes_summary', 'explicit', 'feed_url'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
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   "source": [
    "# guess language based on itunes_summary\n",
    "lang_guess = []\n",
    "for x in podcastDf['itunes_summary']:\n",
    "    lang_guess.append(guess_language.guessLanguageName(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
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   "source": [
    "podcastDf['language'] = pd.Series(lang_guess, index = podcastDf.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
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   "outputs": [],
   "source": [
    "# keep only English podcasts\n",
    "podcastDf = podcastDf.query(\"language == 'English'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# save df to pickle\n",
    "podcastDf.to_pickle('pkl/english_podcasts.pkl')"
   ]
  }
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