12_01_Data_Visualization.ipynb

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        "# Data visualization\n",
        "\n",
        "An essential part of the scientific process is visualizing the results you have produced.\n",
        "\n",
        "For example, when setting out to answer a research question, a methodology is usually specified. After this methodology has been utilized, the results need to be reported.\n",
        "\n",
        "You may generate lots and lots of results, as this is part of the research process. After which, you may have to select the best data to present as part of the scientific narrative of your paper. These data items require plotting.\n",
        "\n",
        "The easiest way to plot your coursework results is via `Pandas`.\n"
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        "# Plotting in Pandas\n",
        "\n",
        "Once you have your data in a `Pandas` dataframe, you can very easily plot your data.\n",
        "\n",
        "Below are a set of plotting examples which you could utilize for your assignment project.\n",
        "\n",
        "First, each example specifies the input data (which would need adapting for each context), and converts this to a `Pandas` df for plotting.\n",
        "\n",
        "Secondly, we specify the call to the `Pandas` plotting function.\n",
        "\n",
        "Let us begin with a basic bar plot."
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        "# Example: First, we create a basic df for plotting\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# We can create the underlying data for our Pandas df\n",
        "# Here we have route scenarios, and the estimated travel time\n",
        "data_raw = {\n",
        "    'route': ['A', 'B', 'C', 'D'],\n",
        "    'time_hours': [1.5, 0.5, 1, 0.75]\n",
        "  }\n",
        "\n",
        "# Convert to a pandas df\n",
        "data = pd.DataFrame(data_raw)\n",
        "data"
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              "  route  time_hours\n",
              "0     A        1.50\n",
              "1     B        0.50\n",
              "2     C        1.00\n",
              "3     D        0.75"
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              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"route\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"B\",\n          \"D\",\n          \"A\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"time_hours\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.42695628191498325,\n        \"min\": 0.5,\n        \"max\": 1.5,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          0.5,\n          0.75,\n          1.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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        "Now we can call our plotting function using `.plot.bar()`.\n",
        "\n",
        "The in-line code comments should be self explanatory for each argument, e.g., the x axis column, or y axis column, title, etc."
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        "# Now we can plot our barplot data\n",
        "data.plot.bar(\n",
        "    x='route',                          # x axis variable\n",
        "    y='time_hours',                     # y axis variable\n",
        "    title=\"Barplot of Data Values\",     # plot title\n",
        "    rot=0                               # rotate x axis labels\n",
        "  )\n",
        "plt.xlabel('Route Scenario')\n",
        "plt.ylabel('Travel Time (hours)')"
      ],
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              "Text(0, 0.5, 'Travel Time (hours)')"
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              "<Figure size 640x480 with 1 Axes>"
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now you have the hang of the approach we will take (specifying our plotting data, and then plotting), it should be easier to understand how to create more complicated plots.\n",
        "\n",
        "Next, we will look at a dodged barplot containing travel times for either walking or driving via car.  "
      ],
      "metadata": {
        "id": "bHvunSqs_nxM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example: Creating a dodged barplot\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Define our variables\n",
        "walking = [1.5, 2.5, 1.7, 0.75]\n",
        "car = [0.3,0.5,0.4,0.2]\n",
        "route = ['A', 'B', 'C', 'D']\n",
        "\n",
        "# Create our df\n",
        "df = pd.DataFrame({'walking': walking,\n",
        "                   'car': car}, index=route)\n",
        "\n",
        "# Finally, we can plot the data\n",
        "df.plot.bar(\n",
        "    title=\"Dodged Barplot of Travel Time Data Values\",\n",
        "    rot=0\n",
        ")\n",
        "plt.xlabel('Route Scenario')\n",
        "plt.ylabel('Travel Time (hours)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "KDXdiN8aDwv8",
        "outputId": "af7972e4-7a36-4b60-9157-f93d060bbc47"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Travel Time (hours)')"
            ]
          },
          "metadata": {},
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "If we want, we can also create a panel plot, placing each of these data columns on their own separate subplot graph."
      ],
      "metadata": {
        "id": "pAnVuXyLIPWa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example: Creating a panel plot\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Define our variables\n",
        "walking = [1.5, 2.5, 1.7, 0.75]\n",
        "car = [0.3,0.5,0.4,0.2]\n",
        "route = ['A', 'B', 'C', 'D']\n",
        "\n",
        "# Create our df\n",
        "df = pd.DataFrame({'walking': walking,\n",
        "                   'car': car}, index=route)\n",
        "\n",
        "# Finally, we can plot the data\n",
        "df.plot.bar(\n",
        "    title=\"Panel plot of Travel Time Data Values\",\n",
        "    rot=0,\n",
        "    subplots=True\n",
        ")\n",
        "plt.xlabel('Route Scenario')\n",
        "plt.ylabel('Travel Time (hours)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 515
        },
        "id": "Zwl3wOOKEtgF",
        "outputId": "7b6578d6-f04d-45cf-e909-70130c1dd1dc"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Travel Time (hours)')"
            ]
          },
          "metadata": {},
          "execution_count": 53
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally, we can consider a stacked barplot.\n",
        "\n",
        "Stacked barplots are very useful for showing the composition of a set of results.\n",
        "\n",
        "For example, here we plot the potential damage cost by category for a volcano eruption radius."
      ],
      "metadata": {
        "id": "uwta2Zr_Ikb4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example: Creating a stacked barplot\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Define our variables\n",
        "buildings_mn = [5,8,24,36,43]\n",
        "roads_mn = [1,2,3,4,6]\n",
        "distance = ['5 km','10 km','15 km','20 km','25 km']\n",
        "\n",
        "# Create our df\n",
        "df = pd.DataFrame({'buildings': buildings_mn,\n",
        "                   'roads': roads_mn}, index=distance)\n",
        "\n",
        "# Finally, we can plot the data\n",
        "df.plot.bar(\n",
        "    title=\"Volcano Damage Cost\",\n",
        "    rot=0,\n",
        "    stacked=True\n",
        ")\n",
        "plt.xlabel('Volcano Eruption Damage Radius (km)')\n",
        "plt.ylabel('Replacement Cost (US$ Mn)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "gFCv7P6_GoOZ",
        "outputId": "a619dc48-b387-4eb7-bc21-74fb546ba1a8"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Replacement Cost (US$ Mn)')"
            ]
          },
          "metadata": {},
          "execution_count": 59
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}