examples/ch07/snippets_ipynb/07_14.01selfcheck.ipynb

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   "source": [
    "![Self Check Exercises check mark image](files/art/check.png)\n",
    "# 7.14.1 Self Check"
   ]
  },
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   "source": [
    "**1. _(IPython Session)_** Use the NumPy’s random number generation to create an `array` of five random integers that represent summertime temperatures in the range 60–100, then perform the following tasks:\n",
    "\n",
    "**a.** Convert the `array` into the `Series` named `temperatures` and display it.\n",
    "\n",
    "**b.** Determine the lowest, highest and average temperatures.\n",
    "\n",
    "**c.** Produce descriptive statistics for the `Series`. \n",
    "\n",
    "**Answer:** "
   ]
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   "source": [
    "import numpy as np"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "temps = np.random.randint(60, 101, 5)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "temperatures = pd.Series(temps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    70\n",
       "1    63\n",
       "2    76\n",
       "3    72\n",
       "4    87\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatures"
   ]
  },
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     "data": {
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       "63"
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     "execution_count": 6,
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   "source": [
    "temperatures.min()"
   ]
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "87"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatures.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73.6"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatures.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     5.000000\n",
       "mean     73.600000\n",
       "std       8.848729\n",
       "min      63.000000\n",
       "25%      70.000000\n",
       "50%      72.000000\n",
       "75%      76.000000\n",
       "max      87.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temperatures.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##########################################################################\n",
    "# (C) Copyright 2019 by Deitel & Associates, Inc. and                    #\n",
    "# Pearson Education, Inc. All Rights Reserved.                           #\n",
    "#                                                                        #\n",
    "# DISCLAIMER: The authors and publisher of this book have used their     #\n",
    "# best efforts in preparing the book. These efforts include the          #\n",
    "# development, research, and testing of the theories and programs        #\n",
    "# to determine their effectiveness. The authors and publisher make       #\n",
    "# no warranty of any kind, expressed or implied, with regard to these    #\n",
    "# programs or to the documentation contained in these books. The authors #\n",
    "# and publisher shall not be liable in any event for incidental or       #\n",
    "# consequential damages in connection with, or arising out of, the       #\n",
    "# furnishing, performance, or use of these programs.                     #\n",
    "##########################################################################\n"
   ]
  }
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