Python编写一个B树类，实现以下功能：读取“电影评分数据.xlsx”的“Split Rows”页，列名分别为“Title”“Overview”“genre”“Vote Average”“Vote Count”，根据电影评分记录中的“Vote Average”属性值构建B树索引。根据B树索引实现电影评分“Vote Average”的范围查询，如果评分“Vote Average”相同，则根据“Vote Count”属性值降序排序，把排序后范围内的电影的所有信息（包括“Title”“Overview”“genre”“Vote Average”“Vote Count”）保存到“result_3.csv”里。例如查询所有评分在5.5-6.7之间的电影

[i][0]:
i += 1
if i < len(x.keys) and k == x.keys[i][0]:
return x.keys[i]
elif x.leaf:
return None
else:
return self.search(k, x.child[i])
else以下是一个使用Python编写的B树类，实现了您所描述的功能：

import pandas as pd

:
            return self.search(k, self.root)

    def range_query(self, start, end, x=None):
        if isinstance(x, Bclass BTreeNode:
    def __init__(self, leaf=False):
        self.leaf = leaf
        self.keys = []
        self.childTreeNode):
            results = []
            i = 0
            while i < len(x.keys) and start > x.keys[i][0]:
 = []

class BTree:
    def __init__(self, t):
        self.root = BTreeNode(True)
        self.t = t

                i += 1
            if x.leaf:
                while i < len(x.keys) and start <= x.keys[i][0]    def insert(self, k):
        root = self.root
        if len(root.keys) == (2 * self.t) - 1 <= end:
                    results.append(x.keys[i])
                    i += 1
            elif i < len(x.keys) and start <= x.keys:
            temp = BTreeNode()
            self.root = temp
            temp.child.insert(0, root)
            self.split_child(temp, [i][0]:
                results.extend(self.range_query(start, end, x.child[i]))
            if i < len(x.child):
                results.extend0)
            self.insert_non_full(temp, k)
        else:
            self.insert_non_full(root, k)

    def insert_non_full(self(self.range_query(start, end, x.child[i]))
            return results
        else:
            return self.range_query(start, end, self.root, x, k):
        i = len(x.keys) - 1
        if x.leaf:
            x.keys.append((None,)

def create_btree(file_path):
    # 读取电影评分数据
    df = pd.read_excel(file_path, sheet None, None, k))
            x.keys.sort(key=lambda tup: (tup[3], -tup[4]), reverse=True)
_name='Split Rows')
    movie_records = df[['Title', 'Overview', 'genre', 'Vote Average', 'Vote Count']].values.tolist        else:
            while i >= 0 and k < x.keys[i][3]:
                i -= 1
            i += 1()

    # 创建B树索引
    btree = BTree(t=3)  # 设置B树的度为3

            if len(x.child[i].keys) == (2 * self.t) - 1:
                self.split_child(x, i)
    for record in movie_records:
        key = (record[3], record[4])  # 评分和评分数量组                if k > x.keys[i][3]:
                    i += 1
            self.insert_non_full(x.child[i], k)

    def成键值
        btree.insert(key)

    return btree

def save_results(results, file_path):
    with open(file_path, split_child(self, x, i):
        t = self.t
        y = x.child[i]
        z = BTreeNode(y.leaf 'w', newline='', encoding='utf-8') as csvfile:
        writer = csv.writer(csvfile)
        writer.writerow(['Title', ')
        x.child.insert(i + 1, z)
        x.keys.insert(i, y.keys[t - 1])
        z.keys =Overview', 'genre', 'Vote Average', 'Vote Count'])
        writer.writerows(results)

if __name__ == '__main__':
    b y.keys[t: (2 * t) - 1]
        y.keys = y.keys[0: t - 1]
        iftree = create_btree('电影评分数据.xlsx')
    results = btree.range_query(5.5, 6.7 not y.leaf:
            z.child = y.child[t: 2 * t]
            y.child = y.child[0: t -)
    save_results(results, 'result_3.csv')

请确保在运行代码之前安装了以下依赖 1]

def range_query(self, x, min_val, max_val, result):
i = 0
while i <库：
- pandas
- csv

该代码会读取名为"电影评分数据.xlsx"的文件中的"Split len(x.keys) and min_val > x.keys[i][3]:
i += 1
if x.leaf:
while i Rows"页，提取相关列的数据并构建B树索引。然后，它将执行范围查询，找 < len(x.keys) and min_val <= x.keys[i][3] <= max_val:
result.append(x.keys[i])
i +=到评分在指定范围内的电影，并将结果保存在名为"result_3.csv"的文件中。