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Added first 4 problems on NumPy Basic
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‎02_NumPy/.ipynb_checkpoints/01_NumPy Basic [41 exercises with solution]-checkpoint.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1.Write a NumPy program to get the numpy version and show numpy build configuration."
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"## 1.Write a NumPy program to get the numpy version and show numpy build configuration."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": []
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"NumPy Version: 1.16.4\n",
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"\n",
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"Configuration:\n",
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"===============\n",
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"mkl_info:\n",
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" libraries = ['mkl_rt']\n",
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" library_dirs = ['C:/ProgramData/Anaconda3\\\\Library\\\\lib']\n",
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" define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
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" include_dirs = ['C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\include', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\lib', 'C:/ProgramData/Anaconda3\\\\Library\\\\include']\n",
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"blas_mkl_info:\n",
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" libraries = ['mkl_rt']\n",
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" library_dirs = ['C:/ProgramData/Anaconda3\\\\Library\\\\lib']\n",
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" define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
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" include_dirs = ['C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\include', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\lib', 'C:/ProgramData/Anaconda3\\\\Library\\\\include']\n",
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"blas_opt_info:\n",
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" libraries = ['mkl_rt']\n",
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" library_dirs = ['C:/ProgramData/Anaconda3\\\\Library\\\\lib']\n",
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" define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
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" include_dirs = ['C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\include', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\lib', 'C:/ProgramData/Anaconda3\\\\Library\\\\include']\n",
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"lapack_mkl_info:\n",
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" libraries = ['mkl_rt']\n",
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" library_dirs = ['C:/ProgramData/Anaconda3\\\\Library\\\\lib']\n",
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" define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
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" include_dirs = ['C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\include', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\lib', 'C:/ProgramData/Anaconda3\\\\Library\\\\include']\n",
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"lapack_opt_info:\n",
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" libraries = ['mkl_rt']\n",
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" library_dirs = ['C:/ProgramData/Anaconda3\\\\Library\\\\lib']\n",
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" define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]\n",
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" include_dirs = ['C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\include', 'C:\\\\Program Files (x86)\\\\IntelSWTools\\\\compilers_and_libraries_2019.0.117\\\\windows\\\\mkl\\\\lib', 'C:/ProgramData/Anaconda3\\\\Library\\\\include']\n",
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"None\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"\n",
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"print('NumPy Version:', np.__version__)\n",
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"print('\\nConfiguration:')\n",
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"print('='*15)\n",
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"print(np.show_config())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 2. Write a NumPy program to get help on the add function."
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"## 2. Write a NumPy program to get help on the add function."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": []
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"add(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])\n",
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"\n",
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"Add arguments element-wise.\n",
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"\n",
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"Parameters\n",
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"----------\n",
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"x1, x2 : array_like\n",
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" The arrays to be added. If ``x1.shape != x2.shape``, they must be\n",
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" broadcastable to a common shape (which may be the shape of one or\n",
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" the other).\n",
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"out : ndarray, None, or tuple of ndarray and None, optional\n",
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" A location into which the result is stored. If provided, it must have\n",
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" a shape that the inputs broadcast to. If not provided or `None`,\n",
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" a freshly-allocated array is returned. A tuple (possible only as a\n",
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" keyword argument) must have length equal to the number of outputs.\n",
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"where : array_like, optional\n",
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" Values of True indicate to calculate the ufunc at that position, values\n",
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" of False indicate to leave the value in the output alone.\n",
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"**kwargs\n",
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" For other keyword-only arguments, see the\n",
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" :ref:`ufunc docs <ufuncs.kwargs>`.\n",
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"\n",
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"Returns\n",
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"-------\n",
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"add : ndarray or scalar\n",
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" The sum of `x1` and `x2`, element-wise.\n",
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" This is a scalar if both `x1` and `x2` are scalars.\n",
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"\n",
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"Notes\n",
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"-----\n",
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"Equivalent to `x1` + `x2` in terms of array broadcasting.\n",
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"\n",
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"Examples\n",
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"--------\n",
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">>> np.add(1.0, 4.0)\n",
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"5.0\n",
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">>> x1 = np.arange(9.0).reshape((3, 3))\n",
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">>> x2 = np.arange(3.0)\n",
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">>> np.add(x1, x2)\n",
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"array([[ 0., 2., 4.],\n",
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" [ 3., 5., 7.],\n",
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" [ 6., 8., 10.]])\n",
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"None\n"
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]
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}
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],
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"source": [
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"print(np.info(np.add))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3. Write a NumPy program to test whether none of the elements of a given array is zero. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": []
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Checking if none of the array emements have 0:\n",
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"False\n",
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"Checking if at least one of the array emement is 0: \n",
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"True\n",
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"Checking if at least one of the array emement is 0: \n",
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"False\n"
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]
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}
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],
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"source": [
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"# Here we mainly checking whether all the elements are non zero or not\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"arr1 = np.array([0, 1, 2, 3])\n",
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"print('Checking if none of the array emements have 0:') # returns 'False' if one of the array element is 0\n",
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"print(np.all(arr1))\n",
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"\n",
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"arr2 = np.array([1, 2, 3, 4])\n",
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"print('Checking if at least one of the array emement is 0: ') # returns 'True' if 0 is not present in the array emements\n",
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"print(np.all(arr2))\n",
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"\n",
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"arr3 = np.array([0, 0, 0, 0])\n",
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"print('Checking if at least one of the array emement is 0: ') # returns 'False' if one of the array element is 0\n",
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"print(np.all(arr3))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 4. Write a NumPy program to test if any of the elements of a given array is non-zero."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Checking if none of the array emements have 0:\n",
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"True\n",
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"Checking if at least one of the array emement is 0: \n",
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"True\n",
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"Checking if at least one of the array emement is 0: \n",
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"False\n"
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]
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}
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],
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"source": [
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"# Here we mainly checking if any of the array elements contains other than '0'\n",
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"\n",
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"import numpy as np\n",
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"\n",
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"arr1 = np.array([0, 1, 2, 3])\n",
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"print('Checking if none of the array emements have 0:') # returns 'True' if one of the array element is not 0\n",
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"print(np.any(arr1))\n",
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"\n",
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"arr2 = np.array([1, 2, 3, 4])\n",
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"print('Checking if at least one of the array emement is 0: ') # returns 'True' if one of the array element is not 0\n",
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"print(np.any(arr2))\n",
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"\n",
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"arr3 = np.array([0, 0, 0, 0])\n",
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"print('Checking if at least one of the array emement is 0: ') # returns 'False' if all of the array element is 0\n",
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"print(np.any(arr3))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 5. Write a NumPy program to test a given array element-wise for finiteness (not infinity or not a Number)."
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]
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},
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{
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"cell_type": "code",

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