How to analyze and visualize epidemic data in PHP?

Epidemic data analysis and visualization has always been a topic that has received widespread attention during the epidemic. When analyzing and visualizing epidemic data in PHP, you can not only obtain the latest epidemic data, but also analyze and display the data through data visualization tools to more intuitively understand the development trend of the epidemic.

This article will briefly introduce how to obtain the latest epidemic data in PHP, and how to use common data visualization tools to analyze and display the data.

1. Obtain epidemic data

Obtaining the latest epidemic data can be achieved through web crawlers. When crawling data, you need to pay attention to some common anti-crawling methods. You can use some simple techniques, such as setting crawler request headers and simulating logins, to avoid anti-crawling.

There are many ways to obtain epidemic data. The following takes crawling the Dingxiangyuan official website (https://ncov.dxy.cn) as an example to introduce how to use PHP to obtain the latest epidemic data.

The specific steps are as follows:

1. Use CURL to send an HTTP request and save the response result as a string.

function get_html($url){
    $ch = curl_init();
    curl_setopt($ch, CURLOPT_URL, $url);
    curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
    $output = curl_exec($ch);
    curl_close($ch);
    return $output;
}

$html = get_html('https://ncov.dxy.cn/ncovh5/view/pneumonia');

2. Use regular expressions to match the required data.

$pattern = '/<script id="getListByCountryTypeService2">(.*?)</script>/si';
preg_match($pattern, $html, $matches);
$matches_str = $matches[1];

3. Convert the matched string into a PHP array.

$matches_str = str_replace('toArray(', '', $matches_str);
$matches_str = str_replace(')', '', $matches_str);
$data_array = json_decode($matches_str, true);

2. Data Visualization

After obtaining the epidemic data, you can use common data visualization tools to analyze and display the data. Echarts is used as a data visualization tool here.

Echarts is a JavaScript data visualization library that supports multiple chart types, including line charts, bar charts, pie charts, etc. Echarts supports integration with PHP. You only need to convert the PHP array into JSON format and pass it to the front end.

The following is the specific implementation process.

1. Introduce the Echarts library into the HTML page.

<script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.min.js"></script>

2. Use PHP arrays to generate JSON format data.

$data = [];
foreach ($data_array as $item) {
    $data[] = [
        'name' => $item['provinceName'],
        'value' => $item['confirmedCount']
    ];
}
$json_data = json_encode($data);

3. Use JavaScript code to pass JSON format data to Echarts and generate a map-type visual chart.

<script type="text/javascript">
    var myChart = echarts.init(document.getElementById('map'));

    var option = {
        visualMap: {
            min: 0,
            max: 80000,
            left: 'left',
            top: 'bottom',
            text: ['高', '低'],
            calculable: true
        },
        toolbox: {
            show: true,
            orient: 'vertical',
            left: 'right',
            top: 'center',
            feature: {
                dataView: {readOnly: false},
                restore: {},
                saveAsImage: {}
            }
        },
        series: [
            {
                name: '确诊人数',
                type: 'map',
                mapType: 'china',
                roam: false,
                label: {
                    normal: {
                        show: true
                    },
                    emphasis: {
                        show: true
                    }
                },
                data:<?php echo $json_data; ?>
            }
        ]
    };

    myChart.setOption(option);
</script>

This code will generate a China map type visual chart showing the number of confirmed cases in each province.

3. Summary

Through the above method, we can easily obtain the latest epidemic data in PHP, and use data visualization tools such as Echarts to analyze and display the data. These tools can help us understand the development trend of the epidemic more intuitively and provide strong data support for epidemic prevention and control.

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