{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 1\n",
    "Import NumPy under the alias `np`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 2\n",
    "Import pandas under the alias `pd`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 3\n",
    "Given the DataFrame `data`, remove all of its rows that contain null values using the pandas method discussed in the lesson."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.DataFrame(np.array([[np.nan, 8, 12],[np.nan, 16, np.nan],[4, 13, 45]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "     0     1     2\n",
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     "execution_count": 4,
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   ],
   "source": [
    "#Solution goes here\n",
    "data.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 4\n",
    "Given the DataFrame `data`, remove all of its columns that contain null values using the pandas method discussed in the lesson."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      1\n",
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     "execution_count": 5,
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   "source": [
    "#Solution goes here\n",
    "data.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 5\n",
    "Given the DataFrame `data`, replace all of its null values with `💩` (copy and paste it)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "   0     1   2\n",
       "0  💩   8.0  12\n",
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   "source": [
    "data.fillna('💩')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 6\n",
    "Given the DataFrame `data`, replace all of its null values with the mean value across the entire DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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   "source": [
    "data.fillna(data.mean())"
   ]
  }
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