{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before you turn this problem in, make sure everything runs as expected. First, **restart the kernel** (in the menubar, select Kernel$\\rightarrow$Restart) and then **run all cells** (in the menubar, select Cell$\\rightarrow$Run All).\n",
    "\n",
    "Make sure you fill in any place that says `YOUR CODE HERE` or \"YOUR ANSWER HERE\", as well as your name and collaborators below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "NAME = \"\"\n",
    "COLLABORATORS = \"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import os.path\n",
    "import pandas as pd\n",
    "\n",
    "datadir = \"publicdata\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "babybyname = pd.read_csv(os.path.join(datadir, \"babybyyear.csv\"))\n",
    "female1 = pd.read_csv(os.path.join(datadir, \"female1.csv\"))\n",
    "male1 = pd.read_csv(os.path.join(datadir, \"male1.csv\"))\n",
    "temps = pd.read_csv(os.path.join(datadir, \"madison_temp.csv\"))\n",
    "temps2 = pd.read_csv(os.path.join(datadir, \"temps2.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_labels = ['I', 'J', '1', '2', '3']\n",
    "row_labels = ['A', 'B', 'C']\n",
    "dataset = [[ 'A.I', 'A.J', 'A.1', 'A.2', 'A.3' ],\n",
    "           [ 'B.I', 'B.J', 'B.1', 'B.2', 'B.3' ],\n",
    "           [ 'C.I', 'C.J', 'C.1', 'C.2', 'C.3' ]]\n",
    "example2 = pd.DataFrame(dataset, columns=column_labels, index=row_labels)\n",
    "example1 = example2.drop('J', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "temps2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example1.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example1.T.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example1.index = ['A', 'B', 'C']\n",
    "example1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
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 "nbformat": 4,
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