misc/unpivot.ipynb

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    "# Unpivot GIS Data\n",
    "\n",
    "GIS analysis and visualizaiton typically needs data with 1 value per row. If your data is structured in columns, you need to 'unpivot' it to convert it to 1 value per row. Note that this will result in duplicate features, but they can be handled well in GIS.\n",
    "\n",
    "Example Excel workbook is structured like this\n",
    "\n",
    "| id | species1 | species2 | .. | value 1 | value 2 | ... |\n",
    "| -- | -------- | -------- | -- | ------- | ------- | --- |\n",
    "| 1  | s1       | s2       | .. | 10     | 20      | ... |\n",
    "\n",
    "This script will convert it to a table like follows\n",
    "\n",
    "\n",
    "| id | species | value |\n",
    "| -- | ------- | ----- |\n",
    "| 1  | s1       | 10   |\n",
    "| 1  | s2       | 20   |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "input = 'original.xlsx'\n",
    "df = pd.read_excel(input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.melt(df, id_vars=['id', 'species1'], value_vars=['value1']).rename(columns = {'value1':'value'})\n",
    "df1 = pd.melt(df, id_vars=['id', 'species2'], value_vars=['value2']).rename(columns = {'value2':'value'})\n",
    "merged = pd.concat([df1, df2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop rows which have null values "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged = merged.dropna(axis=0, how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = 'unpivoted.xlsx'\n",
    "merged.to_excel(output, index=False)"
   ]
  }
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