Create yogesh.md learning github

Dijkstra's.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Dijkstra's.ipynb",
+      "provenance": [],
+      "collapsed_sections": [],
+      "authorship_tag": "ABX9TyO+BKfWeDefYHJBxR6szryR",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/yogeshpal1999/LearningGit/blob/master/Dijkstra's.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Cet_8L2A5nPk",
+        "outputId": "193bf876-94b6-477e-9a08-8abc26437e8c",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "source": [
+        "import sys \n",
+        "   \n",
+        "class Graph(): \n",
+        "   \n",
+        "    def __init__(self, vertices): \n",
+        "        self.V = vertices \n",
+        "        self.graph = [[0 for column in range(vertices)]  \n",
+        "                    for row in range(vertices)] \n",
+        "   \n",
+        "    def printSolution(self, dist): \n",
+        "        print (\"Vertex tDistance from Source\") \n",
+        "        for node in range(self.V): \n",
+        "            print (node, \"t\", dist[node]) \n",
+        "   \n",
+        "    # A utility function to find the vertex with  \n",
+        "    # minimum distance value, from the set of vertices  \n",
+        "    # not yet included in shortest path tree \n",
+        "    def minDistance(self, dist, sptSet): \n",
+        "   \n",
+        "        # Initilaize minimum distance for next node \n",
+        "        min = sys.maxsize \n",
+        "   \n",
+        "        # Search not nearest vertex not in the  \n",
+        "        # shortest path tree \n",
+        "        for v in range(self.V): \n",
+        "            if dist[v] < min and sptSet[v] == False: \n",
+        "                min = dist[v] \n",
+        "                min_index = v \n",
+        "   \n",
+        "        return min_index \n",
+        "   \n",
+        "    # Funtion that implements Dijkstra's single source  \n",
+        "    # shortest path algorithm for a graph represented  \n",
+        "    # using adjacency matrix representation \n",
+        "    def dijkstra(self, src): \n",
+        "   \n",
+        "        dist = [sys.maxsize] * self.V \n",
+        "        dist[src] = 0\n",
+        "        sptSet = [False] * self.V \n",
+        "   \n",
+        "        for cout in range(self.V): \n",
+        "   \n",
+        "            # Pick the minimum distance vertex from  \n",
+        "            # the set of vertices not yet processed.  \n",
+        "            # u is always equal to src in first iteration \n",
+        "            u = self.minDistance(dist, sptSet) \n",
+        "   \n",
+        "            # Put the minimum distance vertex in the  \n",
+        "            # shotest path tree \n",
+        "            sptSet[u] = True\n",
+        "   \n",
+        "            # Update dist value of the adjacent vertices  \n",
+        "            # of the picked vertex only if the current  \n",
+        "            # distance is greater than new distance and \n",
+        "            # the vertex in not in the shotest path tree \n",
+        "            for v in range(self.V): \n",
+        "                if self.graph[u][v] > 0 and sptSet[v] == False and dist[v] > dist[u] + self.graph[u][v]: \n",
+        "                    dist[v] = dist[u] + self.graph[u][v] \n",
+        "   \n",
+        "        self.printSolution(dist) \n",
+        "   \n",
+        "# Driver program \n",
+        "g = Graph(9) \n",
+        "g.graph = [[0, 4, 0, 0, 0, 0, 0, 8, 0], \n",
+        "        [4, 0, 8, 0, 0, 0, 0, 11, 0], \n",
+        "        [0, 8, 0, 7, 0, 4, 0, 0, 2], \n",
+        "        [0, 0, 7, 0, 9, 14, 0, 0, 0], \n",
+        "        [0, 0, 0, 9, 0, 10, 0, 0, 0], \n",
+        "        [0, 0, 4, 14, 10, 0, 2, 0, 0], \n",
+        "        [0, 0, 0, 0, 0, 2, 0, 1, 6], \n",
+        "        [8, 11, 0, 0, 0, 0, 1, 0, 7], \n",
+        "        [0, 0, 2, 0, 0, 0, 6, 7, 0] \n",
+        "        ]; \n",
+        "   \n",
+        "g.dijkstra(0);\n"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Vertex tDistance from Source\n",
+            "0 t 0\n",
+            "1 t 4\n",
+            "2 t 12\n",
+            "3 t 19\n",
+            "4 t 21\n",
+            "5 t 11\n",
+            "6 t 9\n",
+            "7 t 8\n",
+            "8 t 14\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    }
+  ]
+}

Lab1.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Lab1.ipynb",
+      "provenance": [],
+      "authorship_tag": "ABX9TyPr87HGr8fjhkDQRb4G9c8T",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/yogeshpal1999/LearningGit/blob/master/Lab1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "vaOT3P-3zNs-",
+        "outputId": "f602fbcc-0709-4438-de7c-a09b7093ef7e"
+      },
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')"
+      ],
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Mounted at /content/drive\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zwSfkkVezbF3"
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np"
+      ],
+      "execution_count": 2,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "tmsYPtalzfHS",
+        "outputId": "d22962d6-34cb-456c-abb1-9dfbf6d53e6a"
+      },
+      "source": [
+        "df = pd.read_csv('/content/drive/MyDrive/banking /heart.csv')\n",
+        "print(df)\n"
+      ],
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "     age  sex  cp  trestbps  chol  fbs  ...  exang  oldpeak  slope  ca  thal  target\n",
+            "0     63    1   3       145   233    1  ...      0      2.3      0   0     1       1\n",
+            "1     37    1   2       130   250    0  ...      0      3.5      0   0     2       1\n",
+            "2     41    0   1       130   204    0  ...      0      1.4      2   0     2       1\n",
+            "3     56    1   1       120   236    0  ...      0      0.8      2   0     2       1\n",
+            "4     57    0   0       120   354    0  ...      1      0.6      2   0     2       1\n",
+            "..   ...  ...  ..       ...   ...  ...  ...    ...      ...    ...  ..   ...     ...\n",
+            "298   57    0   0       140   241    0  ...      1      0.2      1   0     3       0\n",
+            "299   45    1   3       110   264    0  ...      0      1.2      1   0     3       0\n",
+            "300   68    1   0       144   193    1  ...      0      3.4      1   2     3       0\n",
+            "301   57    1   0       130   131    0  ...      1      1.2      1   1     3       0\n",
+            "302   57    0   1       130   236    0  ...      0      0.0      1   1     2       0\n",
+            "\n",
+            "[303 rows x 14 columns]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "qtBnwUUHzt_V",
+        "outputId": "e00049d7-dfcd-48c3-89ad-777df4c777da"
+      },
+      "source": [
+        "print(list(df))"
+      ],
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target']\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "YxV5IZ2uzznH",
+        "outputId": "59fe3c22-5bba-42a0-c5ce-f6496b2c54c7"
+      },
+      "source": [
+        "print(df.dtypes)"
+      ],
+      "execution_count": 5,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "age           int64\n",
+            "sex           int64\n",
+            "cp            int64\n",
+            "trestbps      int64\n",
+            "chol          int64\n",
+            "fbs           int64\n",
+            "restecg       int64\n",
+            "thalach       int64\n",
+            "exang         int64\n",
+            "oldpeak     float64\n",
+            "slope         int64\n",
+            "ca            int64\n",
+            "thal          int64\n",
+            "target        int64\n",
+            "dtype: object\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    }
+  ]
+}