eoropezaelwood-practice-data-structures.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Earth Analytics Bootcamp - Practice Activity on Data Structures\n",
    "**Author:** Eric Oropezaelwood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import urllib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "boulderMonthlyTemperatures = [0.0, 2.0, 5.0, 9.56, 14.39, 21.72, 16.72, 11.61, 4.89, 0.99]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0, 2.0, 5.0, 9.56, 14.39, 21.72, 16.72, 11.61, 4.89, 0.99, 19.56, 22.78]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boulderMonthlyTemperatures.insert(10,19.56)\n",
    "boulderMonthlyTemperatures.insert(11,22.78)\n",
    "\n",
    "boulderMonthlyTemperatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  0.     2.     5.     9.56  14.39  21.72  16.72  11.61   4.89   0.99\n",
      "  19.56  22.78]\n",
      "[  0.     2.     5.     9.56  14.39  21.72  16.72  11.61   4.89   0.99\n",
      "  19.56  22.78]\n"
     ]
    }
   ],
   "source": [
    "npBoulderMonthlyTemperatures = np.array([0.0, 2.0, 5.0, 9.56, 14.39, 21.72, 16.72, 11.61, 4.89, 0.99, 19.56, 22.78])\n",
    "print(npBoulderMonthlyTemperatures)\n",
    "\n",
    "secondNpArray = np.array(boulderMonthlyTemperatures)\n",
    "print(secondNpArray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/ericdelamancha/Documents/Workspace/Earth-analytics-bootcamp'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# change directory to hw2 directory\n",
    "os.chdir(\"/home/ericdelamancha/Documents/Workspace/Earth-analytics-bootcamp\")\n",
    "\n",
    "# print the current working directory\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "datasets downloaded successfully\n"
     ]
    }
   ],
   "source": [
    "# download .csv containing monthly average snowfall (inches) between 2007-2017 for Boulder, CO\n",
    "urllib.request.urlretrieve(url = \"https://ndownloader.figshare.com/files/12732467\", \n",
    "                           filename = \"data/avgMonthlyTempPractice.txt\")\n",
    "\n",
    "# print message that data downloads were successful\n",
    "print(\"datasets downloaded successfully\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  0.     2.     5.     9.56  14.39  19.56  22.78  21.72  16.72  11.61\n",
      "   4.89   0.99]\n"
     ]
    }
   ],
   "source": [
    "avg_monthly_precip = np.loadtxt(fname = \"/home/ericdelamancha/Documents/Workspace/Earth-analytics-bootcamp/data/avgMonthlyTempPractice.txt\")\n",
    "print(avg_monthly_precip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean of Spring Average Monthly Temperatures: 9.65\n",
      "Mean of Fall Average Monthly Temperatures: 11.0733333333\n"
     ]
    }
   ],
   "source": [
    "sliceOne =np.array(avg_monthly_precip)\n",
    "sliceOne = sliceOne[2:5]\n",
    "sliceOneMean = np.mean(sliceOne)\n",
    "print(\"Mean of Spring Average Monthly Temperatures:\", sliceOneMean)\n",
    "\n",
    "sliceTwo =np.array(avg_monthly_precip)\n",
    "sliceTwo = sliceTwo[8:11]\n",
    "sliceTwoMean = np.mean(sliceTwo)\n",
    "print(\"Mean of Fall Average Monthly Temperatures:\", sliceTwoMean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>January</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>February</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>March</td>\n",
       "      <td>5.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>April</td>\n",
       "      <td>9.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>May</td>\n",
       "      <td>14.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>June</td>\n",
       "      <td>19.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>July</td>\n",
       "      <td>22.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>August</td>\n",
       "      <td>21.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>September</td>\n",
       "      <td>16.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>October</td>\n",
       "      <td>11.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>November</td>\n",
       "      <td>4.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>December</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Month   Temp\n",
       "0     January   0.00\n",
       "1    February   2.00\n",
       "2       March   5.00\n",
       "3       April   9.56\n",
       "4         May  14.39\n",
       "5        June  19.56\n",
       "6        July  22.76\n",
       "7      August  21.72\n",
       "8   September  16.72\n",
       "9     October  11.61\n",
       "10   November   4.89\n",
       "11   December   0.99"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avgMonTempBoulder = pd.DataFrame( columns=[\"Month\", \"Temp\"], data=[ [\"January\", 0.00], [\"February\", 2.00], [\"March\", 5.00], [\"April\", 9.56], [\"May\", 14.39], [\"June\", 19.56], [\"July\", 22.76], [\"August\", 21.72], [\"September\", 16.72], [\"October\", 11.61], [\"November\", 4.89], [\"December\", 0.99] ] )\n",
    "avgMonTempBoulder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "datasets downloaded successfully\n"
     ]
    }
   ],
   "source": [
    "# download .csv containing monthly average snowfall (inches) between 2007-2017 for Boulder, CO\n",
    "urllib.request.urlretrieve(url = \"https://ndownloader.figshare.com/files/12739457\", \n",
    "                           filename = \"data/avg-temp-month-seasons.csv\")\n",
    "\n",
    "# print message that data downloads were successful\n",
    "print(\"datasets downloaded successfully\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>months</th>\n",
       "      <th>temp</th>\n",
       "      <th>seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jan</td>\n",
       "      <td>0.00</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Feb</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mar</td>\n",
       "      <td>5.00</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apr</td>\n",
       "      <td>9.56</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>May</td>\n",
       "      <td>14.39</td>\n",
       "      <td>Spring</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>June</td>\n",
       "      <td>19.56</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>July</td>\n",
       "      <td>22.78</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Aug</td>\n",
       "      <td>21.72</td>\n",
       "      <td>Summer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sept</td>\n",
       "      <td>16.72</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Oct</td>\n",
       "      <td>11.61</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Nov</td>\n",
       "      <td>4.89</td>\n",
       "      <td>Fall</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Dec</td>\n",
       "      <td>0.99</td>\n",
       "      <td>Winter</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   months   temp seasons\n",
       "0     Jan   0.00  Winter\n",
       "1     Feb   2.00  Winter\n",
       "2     Mar   5.00  Spring\n",
       "3     Apr   9.56  Spring\n",
       "4     May  14.39  Spring\n",
       "5    June  19.56  Summer\n",
       "6    July  22.78  Summer\n",
       "7     Aug  21.72  Summer\n",
       "8    Sept  16.72    Fall\n",
       "9     Oct  11.61    Fall\n",
       "10    Nov   4.89    Fall\n",
       "11    Dec   0.99  Winter"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_temp_pandas = pd.read_csv(\"/home/ericdelamancha/Documents/Workspace/Earth-analytics-bootcamp/data/avg-temp-month-seasons.csv\")\n",
    "avg_temp_pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>months</th>\n",
       "      <th>temp</th>\n",
       "      <th>seasons</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [months, temp, seasons]\n",
       "Index: []"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_temp_pandas.loc['Winter':]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}