5. Data Types and Missing Values Exercise.ipynb

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   "source": [
    "**This notebook is an exercise in the [Pandas](https://www.kaggle.com/learn/pandas) course.  You can reference the tutorial at [this link](https://www.kaggle.com/residentmario/data-types-and-missing-values).**\n",
    "\n",
    "---\n"
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   "source": [
    "# Introduction\n",
    "\n",
    "Run the following cell to load your data and some utility functions."
   ]
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     "text": [
      "Setup complete.\n"
     ]
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   "source": [
    "import pandas as pd\n",
    "\n",
    "reviews = pd.read_csv(\"../input/wine-reviews/winemag-data-130k-v2.csv\", index_col=0)\n",
    "\n",
    "from learntools.core import binder; binder.bind(globals())\n",
    "from learntools.pandas.data_types_and_missing_data import *\n",
    "print(\"Setup complete.\")"
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   "source": [
    "# Exercises"
   ]
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   "source": [
    "## 1. \n",
    "What is the data type of the `points` column in the dataset?"
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       "Correct"
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    "# Your code here\n",
    "dtype = reviews.points.dtype\n",
    "\n",
    "# Check your answer\n",
    "q1.check()"
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   "source": [
    "#q1.hint()\n",
    "#q1.solution()"
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    "## 2. \n",
    "Create a Series from entries in the `points` column, but convert the entries to strings. Hint: strings are `str` in native Python."
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    "point_strings = reviews.points.astype('str')\n",
    "\n",
    "# Check your answer\n",
    "q2.check()"
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   "source": [
    "#q2.hint()\n",
    "#q2.solution()"
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   "source": [
    "## 3.\n",
    "Sometimes the price column is null. How many reviews in the dataset are missing a price?"
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    "n_missing_prices = reviews.price.isnull().sum()\n",
    "\n",
    "# Check your answer\n",
    "q3.check()"
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    "#q3.hint()\n",
    "#q3.solution()"
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   "source": [
    "## 4.\n",
    "What are the most common wine-producing regions? Create a Series counting the number of times each value occurs in the `region_1` field. This field is often missing data, so replace missing values with `Unknown`. Sort in descending order.  Your output should look something like this:\n",
    "\n",
    "```\n",
    "Unknown                    21247\n",
    "Napa Valley                 4480\n",
    "                           ...  \n",
    "Bardolino Superiore            1\n",
    "Primitivo del Tarantino        1\n",
    "Name: region_1, Length: 1230, dtype: int64\n",
    "```"
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   "source": [
    "reviews_per_region = reviews.region_1.fillna('Unknown').value_counts().sort_values(ascending = False)\n",
    "\n",
    "# Check your answer\n",
    "q4.check()"
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   "source": [
    "#q4.hint()\n",
    "#q4.solution()"
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    "tags": []
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   "source": [
    "# Keep going\n",
    "\n",
    "Move on to **[renaming and combining](https://www.kaggle.com/residentmario/renaming-and-combining)**."
   ]
  },
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   "source": [
    "---\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "*Have questions or comments? Visit the [course discussion forum](https://www.kaggle.com/learn/pandas/discussion) to chat with other learners.*"
   ]
  }
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