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    "<img src=\"http://imgur.com/1ZcRyrc.png\" style=\"float: left; margin: 20px; height: 55px\">\n",
    "\n",
    "## Homework: Intro to Pandas\n",
    "\n",
    "_Author: Kevin Coyle (L.A.)_\n",
    "\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Welcome!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Pandas: Intro Practice Problems\n",
    "\n",
    "In this homework, you're going to write code for a few problems. \n",
    "\n",
    "You'll be practicing these programming concepts we've covered in class:\n",
    "* Reading data sets into Pandas.\n",
    "* Filtering, manipulating, and sorting data sets.\n",
    "* Basic exploratory data analysis with Pandas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### #1. Import Pandas with an alias of `pd`."
   ]
  },
  {
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### #2. Read in the NBA players `csv` into a variable called `nba_df`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a data set of NBA players from 2015. The filename is `NBA_players_2015.csv`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "#### #3. Look at the first five rows of the data set."
   ]
  },
  {
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  },
  {
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   "source": [
    "#### #4. Check out the shape of the data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
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  },
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   "source": [
    "#### #5. Run some summary stats on the data set with the `describe()` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
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   "source": [
    "#### #6. Sort the data set in on the `players` column in alphabetical order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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  },
  {
   "cell_type": "markdown",
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   "source": [
    "#### #7. Filter the data set. Create three sub DataFrames from the `position` column for `G`, `F`, and `C`."
   ]
  },
  {
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   "execution_count": null,
   "metadata": {
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   "source": [
    "#### #8.  Run `describe()` on these new DataFrames. Compare the mean field goals (the `fg` column) between positions."
   ]
  },
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   "execution_count": null,
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The end!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Great job!"
   ]
  }
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