diff --git a/notebooks/Preliminaries_Numpy_Pandas/Jupyter Notebook - Introduction Numpy and Pandas.ipynb b/notebooks/Preliminaries_Numpy_Pandas/Jupyter Notebook - Introduction Numpy and Pandas.ipynb index 00809b7846b9dbe89721c0323a4b6220f437aeaf..6001ae22d0348884b6d15fb61405d54d1b96da6c 100644 --- a/notebooks/Preliminaries_Numpy_Pandas/Jupyter Notebook - Introduction Numpy and Pandas.ipynb +++ b/notebooks/Preliminaries_Numpy_Pandas/Jupyter Notebook - Introduction Numpy and Pandas.ipynb @@ -1871,7 +1871,7 @@ }, { "cell_type": "code", - "execution_count": 283, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -1907,7 +1907,7 @@ }, { "cell_type": "code", - "execution_count": 296, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -1973,26 +1973,26 @@ }, { "cell_type": "code", - "execution_count": 298, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[<matplotlib.axis.YTick at 0x7f070290c250>,\n", - " <matplotlib.axis.YTick at 0x7f070290e810>,\n", - " <matplotlib.axis.YTick at 0x7f0703fc39d0>,\n", - " <matplotlib.axis.YTick at 0x7f07028fa710>,\n", - " <matplotlib.axis.YTick at 0x7f07028fa6d0>,\n", - " <matplotlib.axis.YTick at 0x7f07028e8350>,\n", - " <matplotlib.axis.YTick at 0x7f07028fadd0>,\n", - " <matplotlib.axis.YTick at 0x7f0702882150>,\n", - " <matplotlib.axis.YTick at 0x7f07028825d0>,\n", - " <matplotlib.axis.YTick at 0x7f0702882b90>,\n", - " <matplotlib.axis.YTick at 0x7f070288b110>]" + "[<matplotlib.axis.YTick at 0x7f096f2f5e50>,\n", + " <matplotlib.axis.YTick at 0x7f096f2f54d0>,\n", + " <matplotlib.axis.YTick at 0x7f097d868fd0>,\n", + " <matplotlib.axis.YTick at 0x7f096f26f310>,\n", + " <matplotlib.axis.YTick at 0x7f096f26f210>,\n", + " <matplotlib.axis.YTick at 0x7f096f26ff50>,\n", + " <matplotlib.axis.YTick at 0x7f096f2751d0>,\n", + " <matplotlib.axis.YTick at 0x7f096f2752d0>,\n", + " <matplotlib.axis.YTick at 0x7f096f275810>,\n", + " <matplotlib.axis.YTick at 0x7f096f27d3d0>,\n", + " <matplotlib.axis.YTick at 0x7f096f275410>]" ] }, - "execution_count": 298, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -2073,7 +2073,7 @@ }, { "cell_type": "code", - "execution_count": 300, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -2144,7 +2144,7 @@ }, { "cell_type": "code", - "execution_count": 302, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -2201,7 +2201,7 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -2242,7 +2242,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -2256,9 +2256,9 @@ "Max index: 2\n", "\n", "Use numpy to create a [3,3] dimension array with random number\n", - "[[0.55382541 0.36160037 0.68662274]\n", - " [0.35028249 0.09885074 0.38463975]\n", - " [0.10113939 0.74698869 0.02460112]]\n" + "[[0.48561168 0.60381055 0.21083223]\n", + " [0.13291895 0.83313963 0.32659584]\n", + " [0.797164 0.87792929 0.74653135]]\n" ] } ], diff --git a/notebooks/Preliminaries_Numpy_Pandas/Solution - Basics Numpy.ipynb b/notebooks/Preliminaries_Numpy_Pandas/Solution - Basics Numpy.ipynb index ca42d08c95173392d43105b766e19d5f440d1131..0a03b29bb40e9bcd8e716b3deea6ee104725ac3c 100644 --- a/notebooks/Preliminaries_Numpy_Pandas/Solution - Basics Numpy.ipynb +++ b/notebooks/Preliminaries_Numpy_Pandas/Solution - Basics Numpy.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -83,6 +83,7 @@ "output_type": "stream", "text": [ "Input as Array: [[-1 2 7]]\n", + "Dimension of Input Array: 2\n", "Input minus min: [[0 3 8]]\n", "Input Array: [[0. 0.38 1. ]]\n", "Multiply 1:\n", @@ -100,6 +101,7 @@ "\n", "input_array, inputs_minus_min, inputs_div_max = prepare_inputs([-1,2,7])\n", "print(\"Input as Array: {}\".format(input_array))\n", + "print(\"Dimension of Input Array: {}\".format(input_array.ndim))\n", "print(\"Input minus min: {}\".format(inputs_minus_min))\n", "print(\"Input Array: {}\".format(inputs_div_max))\n", "\n",