移动应用数据统计工具如何创建

# 示例：使用Python进行数据处理
import pandas as pd

def process_data(raw_data):
    df = pd.DataFrame(raw_data)
    df['timestamp'] = pd.to_datetime(df['timestamp'])
    df = df.dropna()
    return df

# 示例：使用Python进行数据分析
from sklearn.cluster import KMeans

def analyze_user_behavior(data):
    kmeans = KMeans(n_clusters=3)
    clusters = kmeans.fit_predict(data[['usage_time', 'click_count']])
    data['cluster'] = clusters
    return data

<!-- 示例：使用Chart.js进行数据可视化 -->
<canvas id="myChart"></canvas>
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script>
    var ctx = document.getElementById('myChart').getContext('2d');
    var myChart = new Chart(ctx, {
        type: 'bar',
        data: {
            labels: ['January', 'February', 'March', 'April', 'May', 'June', 'July'],
            datasets: [{
                label: '# of Votes',
                data: [12, 19, 3, 5, 2, 3, 7],
                backgroundColor: 'rgba(75, 192, 192, 0.2)',
                borderColor: 'rgba(75, 192, 192, 1)',
                borderWidth: 1
            }]
        },
        options: {
            scales: {
                y: {
                    beginAtZero: true
                }
            }
        }
    });
</script>