Visualise_distributions_species_of_iris.ipynb

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  "metadata": {
    "colab": {
      "name": "Visualise distributions - species of iris.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMNmAnT+1CyQS6nowJN9M2M",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/natnew/Python-Projects-Data-Visualisation/blob/main/Visualise_distributions_species_of_iris.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Load Libraries"
      ],
      "metadata": {
        "id": "cJV1SKMdASY8"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "99mC3I_m__WX",
        "outputId": "0e5ade16-9f89-4477-97e1-1b4cd3cbd063"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setup Complete\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "pd.plotting.register_matplotlib_converters()\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "print(\"Setup Complete\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Load and Examine Data"
      ],
      "metadata": {
        "id": "V7RD7wplAg1c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Path of the file to read\n",
        "iris_filepath = ('iris.csv')\n",
        "\n",
        "# Read the file into a variable iris_data\n",
        "iris_data = pd.read_csv(iris_filepath, index_col=\"Id\")\n",
        "\n",
        "# Print the first 5 rows of the data\n",
        "iris_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "33jMDhECAivm",
        "outputId": "9652c44e-3631-4983-9e85-b0752443104d"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sepal Length (cm)</th>\n",
              "      <th>Sepal Width (cm)</th>\n",
              "      <th>Petal Length (cm)</th>\n",
              "      <th>Petal Width (cm)</th>\n",
              "      <th>Species</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ],
            "text/plain": [
              "    Sepal Length (cm)  Sepal Width (cm)  ...  Petal Width (cm)      Species\n",
              "Id                                       ...                               \n",
              "1                 5.1               3.5  ...               0.2  Iris-setosa\n",
              "2                 4.9               3.0  ...               0.2  Iris-setosa\n",
              "3                 4.7               3.2  ...               0.2  Iris-setosa\n",
              "4                 4.6               3.1  ...               0.2  Iris-setosa\n",
              "5                 5.0               3.6  ...               0.2  Iris-setosa\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Plot a histogram"
      ],
      "metadata": {
        "id": "9WGoeQfoAqgF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Histogram \n",
        "sns.distplot(a=iris_data['Petal Length (cm)'], kde=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "k3xswVG4AtAw",
        "outputId": "00c813cd-e36b-4b07-fce1-6fca45feca90"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0b646361d0>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Plot a Density Plot"
      ],
      "metadata": {
        "id": "uqELwKaQAw3-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# KDE plot \n",
        "sns.kdeplot(data=iris_data['Petal Length (cm)'], shade=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "gerUW4zzAytH",
        "outputId": "f9a96a51-9fc6-4e39-d9f3-0448e7f2c139"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0b6461f8d0>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Plot 2D KDE Plot"
      ],
      "metadata": {
        "id": "ziJjaJl5A3N1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 2D KDE plot\n",
        "sns.jointplot(x=iris_data['Petal Length (cm)'], y=iris_data['Sepal Width (cm)'], kind=\"kde\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "id": "I8rzCXPOA9ip",
        "outputId": "c6500173-aaf8-42a3-f4d9-c34c45a8a68f"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7f0b64647410>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Plot Colour coded plots"
      ],
      "metadata": {
        "id": "G4kh1awnBAx9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Paths of the files to read\n",
        "iris_set_filepath = ('iris.csv')\n",
        "iris_ver_filepath = ('iris_versicolor.csv')\n",
        "iris_vir_filepath = ('iris_virginica.csv')\n",
        "\n",
        "# Read the files into variables \n",
        "iris_set_data = pd.read_csv(iris_set_filepath, index_col=\"Id\")\n",
        "iris_ver_data = pd.read_csv(iris_ver_filepath, index_col=\"Id\")\n",
        "iris_vir_data = pd.read_csv(iris_vir_filepath, index_col=\"Id\")\n",
        "\n",
        "# Print the first 5 rows of the Iris versicolor data\n",
        "iris_ver_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "nr96zEbzBC8L",
        "outputId": "550e73f1-5d39-4e78-f549-d8be962a322a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-07fcb1a5-ec27-427f-a6f8-58987615264c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Sepal Length (cm)</th>\n",
              "      <th>Sepal Width (cm)</th>\n",
              "      <th>Petal Length (cm)</th>\n",
              "      <th>Petal Width (cm)</th>\n",
              "      <th>Species</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Id</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>7.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>4.7</td>\n",
              "      <td>1.4</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>6.4</td>\n",
              "      <td>3.2</td>\n",
              "      <td>4.5</td>\n",
              "      <td>1.5</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>6.9</td>\n",
              "      <td>3.1</td>\n",
              "      <td>4.9</td>\n",
              "      <td>1.5</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>5.5</td>\n",
              "      <td>2.3</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.3</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>6.5</td>\n",
              "      <td>2.8</td>\n",
              "      <td>4.6</td>\n",
              "      <td>1.5</td>\n",
              "      <td>Iris-versicolor</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "          document.querySelector('#df-07fcb1a5-ec27-427f-a6f8-58987615264c button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-07fcb1a5-ec27-427f-a6f8-58987615264c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    Sepal Length (cm)  Sepal Width (cm)  ...  Petal Width (cm)          Species\n",
              "Id                                       ...                                   \n",
              "51                7.0               3.2  ...               1.4  Iris-versicolor\n",
              "52                6.4               3.2  ...               1.5  Iris-versicolor\n",
              "53                6.9               3.1  ...               1.5  Iris-versicolor\n",
              "54                5.5               2.3  ...               1.3  Iris-versicolor\n",
              "55                6.5               2.8  ...               1.5  Iris-versicolor\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Histograms for each species\n",
        "sns.distplot(a=iris_set_data['Petal Length (cm)'], label=\"Iris-setosa\", kde=False)\n",
        "sns.distplot(a=iris_ver_data['Petal Length (cm)'], label=\"Iris-versicolor\", kde=False)\n",
        "sns.distplot(a=iris_vir_data['Petal Length (cm)'], label=\"Iris-virginica\", kde=False)\n",
        "\n",
        "# Add title\n",
        "plt.title(\"Histogram of Petal Lengths, by Species\")\n",
        "\n",
        "# Force legend to appear\n",
        "plt.legend()"
      ],
      "metadata": {
        "id": "F-c05JR9Bc7G",
        "outputId": "9b8de49d-48ce-4a28-ecc4-afbcc254898e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f0b6443a0d0>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# KDE plots for each species\n",
        "sns.kdeplot(data=iris_set_data['Petal Length (cm)'], label=\"Iris-setosa\", shade=True)\n",
        "sns.kdeplot(data=iris_ver_data['Petal Length (cm)'], label=\"Iris-versicolor\", shade=True)\n",
        "sns.kdeplot(data=iris_vir_data['Petal Length (cm)'], label=\"Iris-virginica\", shade=True)\n",
        "\n",
        "# Add title\n",
        "plt.title(\"Distribution of Petal Lengths, by Species\")"
      ],
      "metadata": {
        "id": "FmQp7gqeBgjw",
        "outputId": "ce240746-83a1-49b2-d574-1cacac1744d2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        }
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribution of Petal Lengths, by Species')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}