seaborn_exercise.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "seaborn_exercise.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOvu3jTOKdcYMIIqYMqkH/3",
      "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/subhamghimire/Machine-Learning/blob/master/seaborn_exercise.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i4W_CXT_dtzf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N0iAFZAfdxtD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jgpgAr9gdz0_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sns.set_style('whitegrid')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lgDbiVNzeJC1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 215
        },
        "outputId": "2487ec32-8d7d-43a4-dfa4-a081da890a2d"
      },
      "source": [
        "titanic = sns.load_dataset('titanic')\n",
        "titanic.head()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>survived</th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>class</th>\n",
              "      <th>who</th>\n",
              "      <th>adult_male</th>\n",
              "      <th>deck</th>\n",
              "      <th>embark_town</th>\n",
              "      <th>alive</th>\n",
              "      <th>alone</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>male</td>\n",
              "      <td>22.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7.2500</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>38.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>71.2833</td>\n",
              "      <td>C</td>\n",
              "      <td>First</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>C</td>\n",
              "      <td>Cherbourg</td>\n",
              "      <td>yes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>female</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7.9250</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>yes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>53.1000</td>\n",
              "      <td>S</td>\n",
              "      <td>First</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>C</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>yes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>male</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8.0500</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   survived  pclass     sex   age  ...  deck  embark_town  alive  alone\n",
              "0         0       3    male  22.0  ...   NaN  Southampton     no  False\n",
              "1         1       1  female  38.0  ...     C    Cherbourg    yes  False\n",
              "2         1       3  female  26.0  ...   NaN  Southampton    yes   True\n",
              "3         1       1  female  35.0  ...     C  Southampton    yes  False\n",
              "4         0       3    male  35.0  ...   NaN  Southampton     no   True\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rF_jb8XweNVm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "ed93bc57-8f08-4aec-aaa6-3c599dcbc883"
      },
      "source": [
        "sns.jointplot(x='fare',y='age',data=titanic)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7fb6709dde80>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "umwmooQZutWK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "97a7d553-1a33-4c14-d49d-e4ee3268ed8e"
      },
      "source": [
        "sns.distplot(titanic['fare'],kde=False,bins=30)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb6721b3748>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lE879CHRu6HN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "253f0a0d-aeb4-4425-b5de-c7475432871b"
      },
      "source": [
        "sns.boxplot(x='class',y='age',data=titanic,palette='rainbow')"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb671ffdb38>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LF6Y7PxxvN0_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "e5039f98-d867-4332-93a9-e01ed5f6f39f"
      },
      "source": [
        "sns.swarmplot(x='class',y='age',data=titanic)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb670b60c50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4uO8ezOAvwAR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "e960d737-8b15-478e-f1e1-48db8571ef13"
      },
      "source": [
        "sns.countplot(x='sex',data=titanic)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb670713550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OVT6POamwEqO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 304
        },
        "outputId": "6356490f-8186-440c-e578-6d2f74640176"
      },
      "source": [
        "titanic.corr()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>survived</th>\n",
              "      <th>pclass</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>adult_male</th>\n",
              "      <th>alone</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>survived</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.338481</td>\n",
              "      <td>-0.077221</td>\n",
              "      <td>-0.035322</td>\n",
              "      <td>0.081629</td>\n",
              "      <td>0.257307</td>\n",
              "      <td>-0.557080</td>\n",
              "      <td>-0.203367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pclass</th>\n",
              "      <td>-0.338481</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.369226</td>\n",
              "      <td>0.083081</td>\n",
              "      <td>0.018443</td>\n",
              "      <td>-0.549500</td>\n",
              "      <td>0.094035</td>\n",
              "      <td>0.135207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>-0.077221</td>\n",
              "      <td>-0.369226</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.308247</td>\n",
              "      <td>-0.189119</td>\n",
              "      <td>0.096067</td>\n",
              "      <td>0.280328</td>\n",
              "      <td>0.198270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sibsp</th>\n",
              "      <td>-0.035322</td>\n",
              "      <td>0.083081</td>\n",
              "      <td>-0.308247</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.414838</td>\n",
              "      <td>0.159651</td>\n",
              "      <td>-0.253586</td>\n",
              "      <td>-0.584471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>parch</th>\n",
              "      <td>0.081629</td>\n",
              "      <td>0.018443</td>\n",
              "      <td>-0.189119</td>\n",
              "      <td>0.414838</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.216225</td>\n",
              "      <td>-0.349943</td>\n",
              "      <td>-0.583398</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fare</th>\n",
              "      <td>0.257307</td>\n",
              "      <td>-0.549500</td>\n",
              "      <td>0.096067</td>\n",
              "      <td>0.159651</td>\n",
              "      <td>0.216225</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.182024</td>\n",
              "      <td>-0.271832</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adult_male</th>\n",
              "      <td>-0.557080</td>\n",
              "      <td>0.094035</td>\n",
              "      <td>0.280328</td>\n",
              "      <td>-0.253586</td>\n",
              "      <td>-0.349943</td>\n",
              "      <td>-0.182024</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.404744</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>alone</th>\n",
              "      <td>-0.203367</td>\n",
              "      <td>0.135207</td>\n",
              "      <td>0.198270</td>\n",
              "      <td>-0.584471</td>\n",
              "      <td>-0.583398</td>\n",
              "      <td>-0.271832</td>\n",
              "      <td>0.404744</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            survived    pclass       age  ...      fare  adult_male     alone\n",
              "survived    1.000000 -0.338481 -0.077221  ...  0.257307   -0.557080 -0.203367\n",
              "pclass     -0.338481  1.000000 -0.369226  ... -0.549500    0.094035  0.135207\n",
              "age        -0.077221 -0.369226  1.000000  ...  0.096067    0.280328  0.198270\n",
              "sibsp      -0.035322  0.083081 -0.308247  ...  0.159651   -0.253586 -0.584471\n",
              "parch       0.081629  0.018443 -0.189119  ...  0.216225   -0.349943 -0.583398\n",
              "fare        0.257307 -0.549500  0.096067  ...  1.000000   -0.182024 -0.271832\n",
              "adult_male -0.557080  0.094035  0.280328  ... -0.182024    1.000000  0.404744\n",
              "alone      -0.203367  0.135207  0.198270  ... -0.271832    0.404744  1.000000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wnsZOOR4wiRs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "outputId": "0d880512-3490-4465-d11a-0c0a7f5ca864"
      },
      "source": [
        "sns.heatmap(titanic.corr(),cmap='coolwarm')"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb66bfd1550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RNYjMyFOyInZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aJc0O9YbxlL3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        },
        "outputId": "85f45f1b-12a4-46e0-83b5-e71907dc4e3b"
      },
      "source": [
        "g = sns.FacetGrid(data=titanic,col='sex')\n",
        "g = g.map(plt.hist,'age')"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x216 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cEcrsTHaxxti",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}