-- 等宽分段示例
SELECT 
  FLOOR(price/10)*10 AS price_range_start,
  FLOOR(price/10)*10+10 AS price_range_end,
  COUNT(*) AS count
FROM products
GROUP BY FLOOR(price/10)
ORDER BY price_range_start;

-- 自定义分段示例
SELECT 
  CASE 
    WHEN price < 50 THEN '0-50'
    WHEN price < 100 THEN '50-100'
    WHEN price < 200 THEN '100-200'
    ELSE '200+'
  END AS price_range,
  COUNT(*) AS count
FROM products
GROUP BY price_range
ORDER BY price_range;

import pandas as pd
import numpy as np

# 示例数据
data = {'value': np.random.randint(0, 1000, 1000)}
df = pd.DataFrame(data)

# 等宽分段
bins = [0, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
labels = ['0-100', '100-200', '200-300', '300-400', '400-500', 
          '500-600', '600-700', '700-800', '800-900', '900-1000']
df['range'] = pd.cut(df['value'], bins=bins, labels=labels)
result = df.groupby('range').size().reset_index(name='count')
print(result)

# 等频分段（四分位数示例）
df['range'] = pd.qcut(df['value'], q=4, labels=['Q1', 'Q2', 'Q3', 'Q4'])
result = df.groupby('range').size().reset_index(name='count')
print(result)

// 示例数据
const data = Array.from({length: 100}, () => Math.floor(Math.random() * 1000));

// 等宽分段
const binSize = 100;
const bins = {};

data.forEach(value => {
  const bin = Math.floor(value / binSize) * binSize;
  const key = `${bin}-${bin + binSize}`;
  bins[key] = (bins[key] || 0) + 1;
});

console.log(bins);

// 自定义分段
const customBins = {
  '0-100': 0,
  '100-200': 0,
  '200-500': 0,
  '500+': 0
};

data.forEach(value => {
  if (value < 100) customBins['0-100']++;
  else if (value < 200) customBins['100-200']++;
  else if (value < 500) customBins['200-500']++;
  else customBins['500+']++;
});

console.log(customBins);