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   "source": [
    "### <center>San Jose State University<br>Department of Applied Data Science<br><br>**DATA 200<br>Computational Programming for Data Analytics**<br><br>Spring 2024<br>Instructor: Ron Mak</center>"
   ]
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   "source": [
    "#### Whereas Python lists are \"similar to\" arrays, `numpy` arrays are true arrays. \n",
    "#### The `numpy` (Numerical Python) library is the most important library for data analytics. You can use the library to create arrays and perform array operations that are much faster than the equivalent list operations. (`numpy` arrays are implemented by optimized compiled C code.)\n",
    "\n",
    "#### Many of the popular data science libraries are based on or depend on `numpy`."
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   "source": [
    "# 7.2 Creating `arrays` from Existing Data "
   ]
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   "source": [
    "import numpy as np"
   ]
  },
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "numbers = np.array([2, 3, 5, 7, 11])"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "type(numbers)"
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    "numbers"
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   "source": [
    "### Multidimensional Arguments"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.array([[1, 2, 3], [4, 5, 6]])"
   ]
  },
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   "execution_count": null,
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   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Additional material (C) Copyright 2023 by Ronald Mak"
   ]
  }
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