Find Strings in DF

quick_find_strings_in_df.ipynb

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    "import pandas as pd\n",
    "import csv\n",
    "from io import StringIO\n",
    "import re\n",
    "\n",
    "csv_text = \"\"\"id,description,sales\n",
    "1, red checkered shirt xl, 10\n",
    "2, green checkered shirt s, 3\n",
    "3, red checkered shirt xl, 10\n",
    "4, brown jumper m , 2\n",
    "5, black t-shirt l, 2\n",
    "6, white t-shirt xl, 5\n",
    "\"\"\"\n",
    "\n",
    "COLORS = 'red green brown black white'.split(' ')\n",
    "SIZES = 'xs s m l xl'.split(' ')\n",
    "TYPES = 'hat t-shirt jumper shirt'.split(' ')\n",
    "\n",
    "CATEGORIES = {'colors':COLORS, 'sizes':SIZES, 'types':TYPES }\n",
    "\n",
    "\n",
    "\n",
    "f = StringIO(csv_text) # allows us to treat a string like a file\n",
    "df = pd.read_csv(f)\n",
    "df.index = df['id']\n",
    "\n",
    "def categorise_description(row, category_items):\n",
    "    for item in category_items: # loop through the defined \"tokens\" above\n",
    "        if item in row: # if the item is the description\n",
    "            return item # return\n",
    "        else:\n",
    "            continue\n",
    "    \n",
    "\n",
    "\n",
    "# looping through the dictionary, categories\n",
    "for category_name, category_items in CATEGORIES.items():\n",
    "    # append a column, category_name\n",
    "    \n",
    "    df[category_name] = df['description'].apply(lambda row: categorise_description(row, category_items))\n",
    "\n",
    "    \n",
    "    \n",
    "# print df\n",
    "df\n",
    "\n",
    "\n",
    "\n"
   ]
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