kaggle房价预测
目录
1 数据
数据可以在kaggle官网下载，也可利用代码进行下载。
kaggle_house_pred_train.csv
kaggle_house_pred_test.csv
2 代码
代码包含两部分，一部分为基础版，另一部分为模型改进版。
import hashlib # 计算SHA1哈希值，加密
import os # 与操作系统进行交互，系统包
import tarfile # 处理.tar文件，解压
import zipfile # 处理.zip文件，解压
import requests # 发送HTTP请求
import numpy as np
import pandas as pd
import torch # 开源的机器学习库
from torch import nn #用于构建神经网络的模块
from d2l import torch as d2l #深度学习
#1.下载和缓存数据
# @save
DATA_HUB = dict() # 创建一个字典，二元组，用于存储数据集的URL和SHA1哈希值
DATA_URL = 'http://d2l-data.s3-accelerate.amazonaws.com/'
#下载数据集
def download(name, cache_dir=os.path.join('..', 'data')): # @save
"""下载一个DATA_HUB中的文件，返回本地文件名"""
# name: 要下载的数据集的名称；cache_dir: 下载文件的缓存目录
assert name in DATA_HUB, f"{name} 不存在于 {DATA_HUB}" # 断言：判断文件是否在data_hub中，否则抛出异常
# SHA-1曾广泛用于确保数据完整性（文件传输或存储前后的值来对比）
url, sha1_hash = DATA_HUB[name] #从字典中取出地址和密钥
os.makedirs(cache_dir, exist_ok=True) # 创建缓存目录，如果目录已存在则不建
#os.path.join 拼接方法，把url以'/'划分，索引值未-1的值，最后一个
fname = os.path.join(cache_dir, url.split('/')[-1]) # 构建完整的本地文件路径
if os.path.exists(fname): # 如果文件已存在于本地
sha1 = hashlib.sha1() # 创建一个SHA1哈希对象
with open(fname, 'rb') as f: # 打开文件
while True:
data = f.read(1048576) # 读取文件内容，每次读取1MB
if not data: # 如果读取到文件末尾
break
sha1.update(data) # 更新哈希对象
if sha1.hexdigest() == sha1_hash: # 如果计算出的哈希值与预期的哈希值匹配
return fname # 返回文件名，表示命中缓存
#如果文件不存在本地
print(f'正在从{url}下载{fname}...') # 输出下载信息
r = requests.get(url, stream=True, verify=True) # 发送GET请求下载文件
with open(fname, 'wb') as f: # 以二进制写入模式打开文件
f.write(r.content) # 将下载的内容写入文件
return fname # 返回下载后的文件名
#解压
def download_extract(name, folder=None): # @save
"""下载并解压zip/tar文件"""
fname = download(name) # 调用之前定义的download函数来下载文件
base_dir = os.path.dirname(fname) # 获取下载文件所在的目录
data_dir, ext = os.path.splitext(fname) # 分离文件名和扩展名
if ext == '.zip':
fp = zipfile.ZipFile(fname, 'r') # 如果是.zip文件，则创建一个ZipFile对象用于解压
elif ext in ('.tar', '.gz'):
fp = tarfile.open(fname, 'r') # 如果是.tar或.gz文件，则创建一个tarfile对象用于解压
else:
assert False, '只有zip/tar文件可以被解压缩' # 如果文件既不是.zip也不是.tar或.gz，则抛出异常
fp.extractall(base_dir) # 解压文件到base_dir目录
# 如果提供了folder参数，则返回base_dir与folder的组合路径，否则返回data_dir
return os.path.join(base_dir, folder) if folder else data_dir
#将数据集从data_hub下载到缓存目录中
def download_all(): # @save
"""下载DATA_HUB中的所有文件"""
for name in DATA_HUB:
download(name) # 对DATA_HUB字典中的每个数据集名称，调用download函数下载文件
#2.访问和读取数据
#训练集
DATA_HUB['kaggle_house_train'] = ( # @save
DATA_URL + 'kaggle_house_pred_train.csv',
'585e9cc93e70b39160e7921475f9bcd7d31219ce')
#测试集
DATA_HUB['kaggle_house_test'] = ( # @save
DATA_URL + 'kaggle_house_pred_test.csv',
'fa19780a7b011d9b009e8bff8e99922a8ee2eb90')
#使用pandas分别加载包含训练数据和测试数据的2个csv文件
train_data = pd.read_csv(download('kaggle_house_train'))
test_data = pd.read_csv(download('kaggle_house_test'))
#打印前四行的前四个和最后两个特征，以及房价（-1）
#print(train_data.iloc[0:4, [0, 1, 2, 3, -3, -2, -1]]) # 最后一个是真实房价（标签），得把它拿出来
#打印前四行的前四个和最后两个特征
#print(test_data.iloc[0:4, [0, 1, 2, 3, -2, -1]])
# 将train_data和test_data合并（concat拼接方法）成all_features，方便下面算均值和方差
# 第一列是ID无用，把它拿掉
# 把训练集中的房间标签去掉
# 测试集中没有房价标签
# 形式：
# 训练集
# 测试集
all_features = pd.concat((train_data.iloc[:, 1:-1], test_data.iloc[:, 1:]))
#3.数据预处理
# 这里把train和test集拿到一起算均值和方差
# 如果是写论文，只能在训练集上拿均值
# pandas的object是python里的str，需要去除后取均值
numeric_features = all_features.dtypes[all_features.dtypes != 'object'].index # 返回数据类型!=object的列索引
# 数值型数据标准化：均值为0，方差为1
all_features[numeric_features] = all_features[numeric_features].apply(
lambda x: (x - x.mean()) / (x.std()))
# 在标准化数据之后，所有均值消失，将缺失值设置为0
# fillna(0)：将所有缺失值替换为0
all_features[numeric_features] = all_features[numeric_features].fillna(0)
# get_dummies 函数通常用于将分类变量(categorical variables)转换为一系列的二进制（0和1）列，也称为独热编码
# “Dummy_na=True”将“na”（缺失值）视为有效的特征值，并为其创建指示符特征（一个额外的二进制列）
all_features = pd.get_dummies(all_features, dummy_na=True)
#由于pandas的原因，shape可能会显示2019.330
#print(all_features.shape)
# 强制转换，原本的代码里没有这一行，报错np的'object'不能转成torch
# 解决的问题：原本的代码试图将 all_features 数组转换为 PyTorch 张量（tensor），但是失败了。
# 因为 PyTorch 无法直接将包含非数值类型（如字符串）的 NumPy 数组转换为张量。
# 通过先将 all_features 转换为全浮点数数组，就可以避免这个问题，因为 PyTorch 可以轻松地将浮点数 NumPy 数组转换为张量。
all_features = all_features.astype(float)
n_train = train_data.shape[0] # 获取 train_data 数据框的行数
#把预处理前合并在一起的train和test数据集，拆分开
train_features = torch.tensor(all_features[:n_train].values, dtype=torch.float32)
test_features = torch.tensor(all_features[n_train:].values, dtype=torch.float32)
train_labels = torch.tensor( # 测试集没有真实房价test_labels
train_data.SalePrice.values.reshape(-1, 1), dtype=torch.float32) # 把train集的SalePrice列拿出来
#4.训练
# 均方误差损失
loss = nn.MSELoss()
# 获取列（特征）数，原则上是331，但由于pandas版本的原因，可能会显示330
in_features = train_features.shape[1]
#print(in_features)
# 单层线性回归
def get_net():
net = nn.Sequential(nn.Linear(in_features, 1)) # 331个输入，1个输出（预测的房价）
return net
#5.预测
# 评估模型性能的指标：log rmse 对数均方根误差（衡量相对差异）
def log_rmse(net, features, labels):
# 预测值（房价）用clamp剪裁到1至正无穷，到1是防止对数计算出问题，到无穷是因为真实的房价∈(1,+无穷)
# clamp 函数将预测值net(features)中的所有小于1的值都被设置为1
# inf代表无穷大（infinity的缩写）
clipped_preds = torch.clamp(net(features), 1, float('inf'))
#均方根误差数学公式
rmse = torch.sqrt(loss(torch.log(clipped_preds), torch.log(labels)))
# 返回计算得到的均方根误差
# .item() 方法用于从包含单个数值的张量中提取该数值
# 只有一个值的时候，取出来
return rmse.item()
# 使用Adam优化算法（小批量随机梯度下降SGD，Adam是比较平滑的SGD）
def train(net, train_features, train_labels, test_features, test_labels,
num_epochs, learning_rate, weight_decay, batch_size):
# 初始化训练集和测试（验证）集的损失列表
train_ls, test_ls = [], []
# 迭代器，每次迭代返回一个batch
train_iter = d2l.load_array((train_features, train_labels), batch_size)
optimizer = torch.optim.Adam(net.parameters(),
lr = learning_rate, # 学习率
weight_decay = weight_decay) # 权重衰减，用于正则化
for epoch in range(num_epochs): # 开始训练模型 # 遍历每个训练周期
for X, y in train_iter: # 遍历每个批量的训练数据
optimizer.zero_grad() # 置0，清除过往梯度
l = loss(net(X), y) # 计算当前批量的损失
l.backward() # 反向传播计算梯度
optimizer.step() # 根据梯度更新模型参数
train_ls.append(log_rmse(net, train_features, train_labels)) # 记录当前周期的训练集损失
if test_labels is not None: # 如果提供了测试（验证）集数据，则记录当前周期的验证误差
test_ls.append(log_rmse(net, test_features, test_labels))
return train_ls, test_ls # 在本节里，在训练调参期间test_ls实际输出的是valid_ls，k_fold()里调用
# 最后的测试集预测用不上test_ls，函数里的test只是为了区别于train，真实的输入并不是test（这个思想很重要）
#6.k折交叉验证
# 指定第i份切片作为验证集验证数据，其余的作为训练集
def get_k_fold_data(k, i, X, y):
assert k > 1 # 确保k大于1，因为至少需要将数据分为两部分
fold_size = X.shape[0] // k # 每个折的大小
X_train, y_train = None, None # 初始化训练数据集和标签
for j in range(k): # 遍历每个折
idx = slice(j * fold_size, (j + 1) * fold_size) # 计算当前折的索引范围，返回结果是数值
X_part, y_part = X[idx, :], y[idx] # 获取当前折叠的数据和标签
if j == i: # 如果当前折是第i个折叠，则将其作为验证集
X_valid, y_valid = X_part, y_part # 做成验证集
elif X_train is None: # 否则，将当前折叠的数据和标签添加到训练集中
X_train, y_train = X_part, y_part # 做成训练集
else:
# cat连接方法
X_train = torch.cat([X_train, X_part], 0) # 沿着第 0 维（行）拼接训练集data
y_train = torch.cat([y_train, y_part], 0) # 拼接训练集label
return X_train, y_train, X_valid, y_valid # 返回训练集+验证集的data+label
#返回训练和验证误差的平均值
def k_fold(k, X_train, y_train, num_epochs, learning_rate, weight_decay,
batch_size):
train_l_sum, valid_l_sum = 0, 0
for i in range(k): # 做k次
data = get_k_fold_data(k, i, X_train, y_train) # 每次拿到第i折
net = get_net()
train_ls, valid_ls = train(net, *data, num_epochs, learning_rate, # *data输入的是train和valid数据
weight_decay, batch_size) # 每次训练拿到两个loss
train_l_sum += train_ls[-1]
valid_l_sum += valid_ls[-1] # 将最后一个 epoch 的训练损失加到总训练损失中
if i == 0:
d2l.plot(list(range(1, num_epochs + 1)), [train_ls, valid_ls],
xlabel='epoch', ylabel='rmse', xlim=[1, num_epochs],
legend=['train', 'valid'], yscale='log')
d2l.plt.show()
print(f'折{i + 1}，训练log rmse{float(train_ls[-1]):f}, '
f'验证log rmse{float(valid_ls[-1]):f}')
return train_l_sum / k, valid_l_sum / k # 求平均误差
#7.模型选择
k, num_epochs, lr, weight_decay, batch_size = 5, 100, 10, 0, 32
train_l, valid_l = k_fold(k, train_features, train_labels, num_epochs, lr,
weight_decay, batch_size)
#print(f'{k}-折验证: 平均训练log rmse: {float(train_l):f}, 'f'平均验证log rmse: {float(valid_l):f}')
# 看K-折交叉验证的结果图，train和valid重合得比较好，说明没有over fitting
# kaggle比赛：主要要做的就是不断地去调第一行的超参数，看平均验证log rmse（核心指标），损失越小越好
#有时一组超参数的训练误差可能非常低，但K折交叉验证的误差要高得多， 这表明模型过拟合了。
#K-折交叉验证的结果图，train和valid重合得比较好，说明没有over fitting
#在整个训练过程中，我们希望监控训练误差和验证误差这两个数字。
#较少的过拟合可能表明现有数据可以支撑一个更强大的模型， 较大的过拟合可能意味着我们可以通过正则化技术来获益。
#8.预测房价
def train_and_pred(train_features, test_features, train_labels, test_data,
num_epochs, lr, weight_decay, batch_size):
net = get_net() # 用上面get_net()选择的线性回归模型
train_ls, _ = train(net, train_features, train_labels, None, None,
num_epochs, lr, weight_decay, batch_size)
d2l.plot(np.arange(1, num_epochs + 1), [train_ls], xlabel='epoch',
ylabel='log rmse', xlim=[1, num_epochs], yscale='log')
print(f'{k}验证：平均训练log rmse：{float(train_ls[-1]):f}，'
f'平均验证log rmse：{float(valid_l):F}')# 训练出模型（得到权重，用于后几行预测）
# 将神经网络应用于测试集
preds = net(test_features).detach().numpy() # 用detach()获取预测结果，确保代码健壮性，转为NumPy数组
# 将结果重新格式化以导出到Kaggle
# 在原本的test_data上新建一列，名为SalePrice
test_data['SalePrice'] = pd.Series(preds.reshape(1, -1)[0]) # reshape成形状(1,n)，[0]就是拿出唯一一行
# 原本test_data有很多列，但这里只拿出'Id'和'SalePrice'，放到新的submission容器里
submission = pd.concat([test_data['Id'], test_data['SalePrice']], axis=1) # axis=1 表示沿着列来拼接
submission.to_csv('submission.csv', index=False) # 结果存在submission.csv文件，kaggle上提交csv有得分
train_and_pred(train_features, test_features, train_labels, test_data, # train features和labels用来训模型
num_epochs, lr, weight_decay, batch_size) # 训出来的模型导入test_features跑出预测值
#模型改进
#参考https://blog.csdn.net/scdifsn/article/details/139561935?spm=1001.2014.3001.5506
#如果m是nn.Linear，则将其权重（m.weight）初始化为正态分布（高斯分布）的随机数，标准差为0.01。
def init_weights(m):
if type(m) == nn.Linear:
nn.init.normal_(m.weight, std=0.01)
#该模型由nn.Flatten()（将输入展平），一个线性层（输入特征数为in_features，输出特征数为512），ReLU激活函数，和另一个线性层（输入特征数为512，输出特征数为1）组成。
#ReLU激活函数：对于进入神经元的来自上一层神经网络的输入向量 x，使用ReLU函数的神经元会输出至下一层神经元或作为整个神经网络的输出（取决现神经元在网络结构中所处位置）。
#net.apply(init_weights) 应用init_weights函数来初始化网络中所有线性层的权重。
def get_net_1():
net = nn.Sequential(nn.Flatten(),
nn.Linear(in_features, 512),
nn.ReLU(),
nn.Linear(512, 1))
net.apply(init_weights)
return net
def k_fold_1(k, X_train, y_train, num_epochs, learning_rate, weight_decay,
batch_size):
train_l_sum, valid_l_sum = 0, 0
for i in range(k):
data = get_k_fold_data(k, i, X_train, y_train)
net = get_net_1()
train_ls, valid_ls = train(net, *data, num_epochs, learning_rate,
weight_decay, batch_size)
train_l_sum += train_ls[-1]
valid_l_sum += valid_ls[-1]
if i == 0:
d2l.plot(list(range(1, num_epochs + 1)), [train_ls, valid_ls],
xlabel='epoch', ylabel='rmse', xlim=[1, num_epochs],
legend=['train', 'valid'], yscale='log')
d2l.plt.show()
print(f'折{i + 1}，训练log rmse{float(train_ls[-1]):f}, '
f'验证log rmse{float(valid_ls[-1]):f}')
return train_l_sum / k, valid_l_sum / k
k, num_epochs, lr, weight_decay, batch_size = 5, 100, 0.01, 300, 32
train_l, valid_l = k_fold_1(k, train_features, train_labels, num_epochs, lr,
weight_decay, batch_size)
print(f'{k}-折验证: 平均训练log rmse: {float(train_l):f}, '
f'平均验证log rmse: {float(valid_l):f}')
def train_and_pred_1(train_features, test_features, train_labels, test_data,
num_epochs, lr, weight_decay, batch_size):
net = get_net_1() # 用上面get_net()选择的线性回归模型
train_ls, _ = train(net, train_features, train_labels, None, None,
num_epochs, lr, weight_decay, batch_size)
d2l.plot(np.arange(1, num_epochs + 1), [train_ls], xlabel='epoch',
ylabel='log rmse', xlim=[1, num_epochs], yscale='log')
print(f'{k}验证：平均训练log rmse：{float(train_ls[-1]):f}，'
f'平均验证log rmse：{float(valid_l):F}')# 训练出模型（得到权重，用于后几行预测）
# 将神经网络应用于测试集
preds = net(test_features).detach().numpy() # 用detach()获取预测结果，确保代码健壮性，转为NumPy数组
# 将结果重新格式化以导出到Kaggle
# 在原本的test_data上新建一列，名为SalePrice
test_data['SalePrice'] = pd.Series(preds.reshape(1, -1)[0]) # reshape成形状(1,n)，[0]就是拿出唯一一行
# 原本test_data有很多列，但这里只拿出'Id'和'SalePrice'，放到新的submission容器里
submission = pd.concat([test_data['Id'], test_data['SalePrice']], axis=1) # axis=1 表示沿着列来拼接
submission.to_csv('submission_模型改进版.csv', index=False) # 结果存在submission.csv文件
train_and_pred_1(train_features, test_features, train_labels, test_data, # train features和labels用来训模型
num_epochs, lr, weight_decay, batch_size) # 训出来的模型导入test_features跑出预测值3 调试记录
| k | num_ epochs | lr | weight _decay | batch _size | K-折交叉验证 | 训练 log rmse | 验证 log rmse |
| 5 | 100 | 5 | 0 | 64 |  | 0.162503 | 0.170357 |
| 5 | 100 | 2 | 0 | 64 |  | 0.261633 | 0.365835 |
| 5 | 100 | 8 | 0 | 64 |  | 0.145777 | 0.162572 |
| 5 | 100 | 10 | 0 | 64 |  | 0.139791 | 0.155917 |
| 5 | 100 | 10 | 0.1 | 64 |  | 0.148870 | 0.168602 |
| 5 | 100 | 10 | 1 | 64 |  | 0.335794 | 0.286485 |
| 5 | 100 | 10 | 0.01 | 64 |  | 0.140442 | 0.156684 |
| 5 | 100 | 10 | 0.001 | 64 |  | 0.140120 | 0.156092 |
| 5 | 100 | 5 | 0.001 | 64 |  | 0.162795 | 0.171169 |
| 5 | 100 | 20 | 0.001 | 64 |  | 0.128712 | 0.147609 |
| 5 | 100 | 8 | 0.001 | 64 |  | 0.146114 | 0.163414 |
| 5 | 100 | 5 | 0 | 32 |  | 0.139136 | 0.155708 |
| 5 | 100 | 5 | 0 | 128 |  | 0.192183 | 0.246566 |
| 5 | 100 | 10 | 0.001 | 64 |  | 0.139884 | 0.156481 |
| 5 | 100 | 5 | 0.001 | 32 |  | 0.138977 | 0.155641 |
| 5 | 100 | 20 | 0 | 32 |  | 0.128835 | 0.147962 |
| 5 | 100 | 10 | 0 | 32 |  | 0.127945 | 0.147207 |
| 5 | 100 | 10 | 0.001 | 32 |  | 0.128614 | 0.147032 |
| 8 | 100 | 10 | 0 | 32 |  | 0.128037 | 0.142846 |
| 5 | 100 | 10 | 0 | 16 |  | 0.124825 | 0.149123 |
| 5 | 500 | 10 | 0 | 32 |  | 0.121226 | 0.173696 |
| 5 | 500 | 5 | 0 | 32 |  | 0.123240 | 0.160028 |
| 5 | 500 | 10 | 0 | 64 |  | 0.122665 | 0.163520 |
| 5 | 500 | 5 | 0 | 64 |  | 0.124166 | 0.151033 |
模型改进后：
| k | num_ epochs | lr | weight _decay | batch _size | K-折交叉验证 | 训练 log rmse | 验证 log rmse |
| 5 | 100 | 0.01 | 300 | 32 |  | 0.108352 | 0.133742 |
4 submission
| Id | SalePrice |
| 1461 | 113785.96 |
| 1462 | 156048.72 |
| 1463 | 181747.12 |
| 1464 | 203121.05 |
| 1465 | 191368.69 |
| 1466 | 171991.34 |
| 1467 | 182439.89 |
| 1468 | 166988.52 |
| 1469 | 193168.55 |
| 1470 | 112137.09 |
| 1471 | 183325.45 |
| 1472 | 96528.35 |
| 1473 | 91684.69 |
| 1474 | 145767.9 |
| 1475 | 92055.09 |
| 1476 | 344705.5 |
| 1477 | 251672.94 |
| 1478 | 304370.25 |
| 1479 | 298895.25 |
| 1480 | 450478.4 |
| 1481 | 310093.5 |
| 1482 | 217878.61 |
| 1483 | 172409.4 |
| 1484 | 167281.73 |
| 1485 | 196833.64 |
| 1486 | 202284.5 |
| 1487 | 312168.5 |
| 1488 | 241076.8 |
| 1489 | 192070.95 |
| 1490 | 244489.17 |
| 1491 | 200983.84 |
| 1492 | 89535.93 |
| 1493 | 207221.56 |
| 1494 | 290943.78 |
| 1495 | 272638.06 |
| 1496 | 243777.11 |
| 1497 | 164740.9 |
| 1498 | 160438.53 |
| 1499 | 161415.48 |
| 1500 | 153257.61 |
| 1501 | 205820.23 |
| 1502 | 150050.36 |
| 1503 | 290245.22 |
| 1504 | 239660.83 |
| 1505 | 225869.83 |
| 1506 | 195727.6 |
| 1507 | 247069.6 |
| 1508 | 198461.84 |
| 1509 | 153404.28 |
| 1510 | 149474.89 |
| 1511 | 143365.73 |
| 1512 | 179771.84 |
| 1513 | 143153.25 |
| 1514 | 164463.28 |
| 1515 | 207142.9 |
| 1516 | 165766.83 |
| 1517 | 174731.44 |
| 1518 | 116633.61 |
| 1519 | 228801.88 |
| 1520 | 120989.82 |
| 1521 | 123662.26 |
| 1522 | 199498.92 |
| 1523 | 94180.74 |
| 1524 | 111497.59 |
| 1525 | 109081.15 |
| 1526 | 98899.4 |
| 1527 | 105529.625 |
| 1528 | 134050.4 |
| 1529 | 147734.1 |
| 1530 | 221878.52 |
| 1531 | 138699.95 |
| 1532 | 106128.23 |
| 1533 | 151896.75 |
| 1534 | 120328.18 |
| 1535 | 147092.66 |
| 1536 | 103856.2 |
| 1537 | 62110.074 |
| 1538 | 168197.88 |
| 1539 | 204008.5 |
| 1540 | 122985.71 |
| 1541 | 146010.6 |
| 1542 | 135174.7 |
| 1543 | 189561.62 |
| 1544 | 81889.63 |
| 1545 | 120721.69 |
| 1546 | 154840.67 |
| 1547 | 133726.47 |
| 1548 | 137232.52 |
| 1549 | 124801.6 |
| 1550 | 148280.11 |
| 1551 | 110953.45 |
| 1552 | 148712.19 |
| 1553 | 161177.12 |
| 1554 | 111970.586 |
| 1555 | 162409.33 |
| 1556 | 74531.97 |
| 1557 | 107806.03 |
| 1558 | 96532.086 |
| 1559 | 74603.625 |
| 1560 | 122241.56 |
| 1561 | 125553.58 |
| 1562 | 128135.73 |
| 1563 | 121719.85 |
| 1564 | 160392.33 |
| 1565 | 157664.53 |
| 1566 | 246291.14 |
| 1567 | 67018.25 |
| 1568 | 244229.27 |
| 1569 | 135903.17 |
| 1570 | 139315.6 |
| 1571 | 98562.34 |
| 1572 | 143781.42 |
| 1573 | 238453.84 |
| 1574 | 129342.39 |
| 1575 | 234006.45 |
| 1576 | 254747.28 |
| 1577 | 186234.83 |
| 1578 | 152971 |
| 1579 | 132953.86 |
| 1580 | 195072.14 |
| 1581 | 160382.27 |
| 1582 | 126756.43 |
| 1583 | 297197.47 |
| 1584 | 225873.42 |
| 1585 | 143116.48 |
| 1586 | 54580.883 |
| 1587 | 96395.14 |
| 1588 | 155891.67 |
| 1589 | 106904.086 |
| 1590 | 118894.31 |
| 1591 | 87651.88 |
| 1592 | 139341.81 |
| 1593 | 132338.28 |
| 1594 | 126392.48 |
| 1595 | 103907.73 |
| 1596 | 220355.9 |
| 1597 | 191195.94 |
| 1598 | 203504.2 |
| 1599 | 183896.42 |
| 1600 | 176789.62 |
| 1601 | 42094.06 |
| 1602 | 122158.266 |
| 1603 | 64171.242 |
| 1604 | 279069.66 |
| 1605 | 244725.19 |
| 1606 | 157484.22 |
| 1607 | 159393.73 |
| 1608 | 221515.55 |
| 1609 | 188232.12 |
| 1610 | 158777.72 |
| 1611 | 140316.42 |
| 1612 | 182707.16 |
| 1613 | 178433.17 |
| 1614 | 133360.28 |
| 1615 | 92409.016 |
| 1616 | 67748.34 |
| 1617 | 81721.27 |
| 1618 | 110459.95 |
| 1619 | 149389.73 |
| 1620 | 178361.98 |
| 1621 | 129779.04 |
| 1622 | 150538.3 |
| 1623 | 266459.34 |
| 1624 | 215463.56 |
| 1625 | 112589.06 |
| 1626 | 188526.47 |
| 1627 | 191013.19 |
| 1628 | 274210.66 |
| 1629 | 172601.25 |
| 1630 | 327413.03 |
| 1631 | 223350.08 |
| 1632 | 229787.77 |
| 1633 | 184525.78 |
| 1634 | 192057.05 |
| 1635 | 179813.38 |
| 1636 | 148082.97 |
| 1637 | 192089.12 |
| 1638 | 190096.72 |
| 1639 | 187786.94 |
| 1640 | 233905.73 |
| 1641 | 180478.47 |
| 1642 | 253303.22 |
| 1643 | 215957.61 |
| 1644 | 232635.14 |
| 1645 | 214740.62 |
| 1646 | 163198.11 |
| 1647 | 156445.33 |
| 1648 | 128814.695 |
| 1649 | 133300.97 |
| 1650 | 118352.555 |
| 1651 | 117679.46 |
| 1652 | 101864.19 |
| 1653 | 101833.8 |
| 1654 | 144298.64 |
| 1655 | 121844.59 |
| 1656 | 138391.4 |
| 1657 | 153000.23 |
| 1658 | 152091.45 |
| 1659 | 115774.8 |
| 1660 | 154700.66 |
| 1661 | 410684.06 |
| 1662 | 346532.53 |
| 1663 | 354381.2 |
| 1664 | 433132.28 |
| 1665 | 307670.03 |
| 1666 | 320085.84 |
| 1667 | 337230.47 |
| 1668 | 337309.9 |
| 1669 | 308173.3 |
| 1670 | 338583.28 |
| 1671 | 269937.66 |
| 1672 | 392537.28 |
| 1673 | 296851.3 |
| 1674 | 253212.11 |
| 1675 | 206520.33 |
| 1676 | 209417.66 |
| 1677 | 223688.92 |
| 1678 | 444021.62 |
| 1679 | 363831.72 |
| 1680 | 317564.28 |
| 1681 | 265073.8 |
| 1682 | 309510.2 |
| 1683 | 195234.47 |
| 1684 | 185219.67 |
| 1685 | 183252.05 |
| 1686 | 172749.53 |
| 1687 | 175924.81 |
| 1688 | 200488.12 |
| 1689 | 203853.39 |
| 1690 | 208397.34 |
| 1691 | 196748.67 |
| 1692 | 265109.97 |
| 1693 | 173670.9 |
| 1694 | 187821.06 |
| 1695 | 165344.77 |
| 1696 | 263436.56 |
| 1697 | 178128.06 |
| 1698 | 324574.88 |
| 1699 | 325771.84 |
| 1700 | 261923.92 |
| 1701 | 270523.2 |
| 1702 | 240113.36 |
| 1703 | 243783.33 |
| 1704 | 274015.34 |
| 1705 | 259214.7 |
| 1706 | 366531.4 |
| 1707 | 221778.94 |
| 1708 | 204072.95 |
| 1709 | 260042.77 |
| 1710 | 225288.2 |
| 1711 | 281397.06 |
| 1712 | 253813.03 |
| 1713 | 270747.25 |
| 1714 | 222348.45 |
| 1715 | 207109.52 |
| 1716 | 178277.83 |
| 1717 | 183508.95 |
| 1718 | 136119.48 |
| 1719 | 217343.42 |
| 1720 | 237617.86 |
| 1721 | 163058.44 |
| 1722 | 117638.375 |
| 1723 | 157007.36 |
| 1724 | 212668.86 |
| 1725 | 234065.83 |
| 1726 | 188661.6 |
| 1727 | 149342.14 |
| 1728 | 176637.75 |
| 1729 | 169230.88 |
| 1730 | 165350.84 |
| 1731 | 117434.9 |
| 1732 | 130452.85 |
| 1733 | 109306.65 |
| 1734 | 114385.72 |
| 1735 | 116077.46 |
| 1736 | 90662.35 |
| 1737 | 302848.88 |
| 1738 | 255245.2 |
| 1739 | 253326.4 |
| 1740 | 221868.5 |
| 1741 | 198871.95 |
| 1742 | 181241.31 |
| 1743 | 184123.56 |
| 1744 | 327130.56 |
| 1745 | 226101.39 |
| 1746 | 191876.45 |
| 1747 | 219786.3 |
| 1748 | 213931.55 |
| 1749 | 134470.95 |
| 1750 | 123112.875 |
| 1751 | 246120.11 |
| 1752 | 109434.8 |
| 1753 | 155650.83 |
| 1754 | 196679.22 |
| 1755 | 174909.73 |
| 1756 | 136186.58 |
| 1757 | 113033.45 |
| 1758 | 154886.48 |
| 1759 | 169205.94 |
| 1760 | 171765.55 |
| 1761 | 168009 |
| 1762 | 184863.5 |
| 1763 | 177031.36 |
| 1764 | 106422.44 |
| 1765 | 170759.22 |
| 1766 | 197105.53 |
| 1767 | 237577.36 |
| 1768 | 138920.52 |
| 1769 | 173282.45 |
| 1770 | 167698.1 |
| 1771 | 114726.08 |
| 1772 | 134439.7 |
| 1773 | 118469.81 |
| 1774 | 157350.5 |
| 1775 | 141197.56 |
| 1776 | 130997.24 |
| 1777 | 102837.67 |
| 1778 | 147411.61 |
| 1779 | 138353.69 |
| 1780 | 178614.1 |
| 1781 | 119641.63 |
| 1782 | 72614.875 |
| 1783 | 157095.02 |
| 1784 | 107546.42 |
| 1785 | 124714.086 |
| 1786 | 147805.27 |
| 1787 | 172646.55 |
| 1788 | 46414.43 |
| 1789 | 103228.516 |
| 1790 | 70055.96 |
| 1791 | 211715.58 |
| 1792 | 165670.83 |
| 1793 | 130794.53 |
| 1794 | 175393.11 |
| 1795 | 125946.83 |
| 1796 | 126382.71 |
| 1797 | 130378.25 |
| 1798 | 118926.41 |
| 1799 | 94789.4 |
| 1800 | 110694.38 |
| 1801 | 121674.73 |
| 1802 | 136749.16 |
| 1803 | 159302.48 |
| 1804 | 129110.59 |
| 1805 | 132420.53 |
| 1806 | 119328.125 |
| 1807 | 151045.97 |
| 1808 | 126432.375 |
| 1809 | 136549.48 |
| 1810 | 144924.53 |
| 1811 | 90992.4 |
| 1812 | 100044.91 |
| 1813 | 123470.25 |
| 1814 | 88850.086 |
| 1815 | 44469.37 |
| 1816 | 92416.92 |
| 1817 | 118327.24 |
| 1818 | 162534.33 |
| 1819 | 122726.92 |
| 1820 | 44784.066 |
| 1821 | 107299.28 |
| 1822 | 160550.75 |
| 1823 | 36294.516 |
| 1824 | 147834.64 |
| 1825 | 144273.84 |
| 1826 | 94870.12 |
| 1827 | 104509.42 |
| 1828 | 143733.2 |
| 1829 | 163778.36 |
| 1830 | 157176.83 |
| 1831 | 146504.78 |
| 1832 | 77893.84 |
| 1833 | 141836.33 |
| 1834 | 114625.49 |
| 1835 | 123055.266 |
| 1836 | 122243.95 |
| 1837 | 81517.82 |
| 1838 | 117950.39 |
| 1839 | 105155.6 |
| 1840 | 159322.58 |
| 1841 | 125149.164 |
| 1842 | 91740.41 |
| 1843 | 142237.55 |
| 1844 | 134637.38 |
| 1845 | 145289.33 |
| 1846 | 149777.58 |
| 1847 | 172309.42 |
| 1848 | 40584.35 |
| 1849 | 124403.586 |
| 1850 | 114246.6 |
| 1851 | 142043.88 |
| 1852 | 117352.336 |
| 1853 | 128320.65 |
| 1854 | 164825.03 |
| 1855 | 141993.39 |
| 1856 | 233386.83 |
| 1857 | 135669.89 |
| 1858 | 130962.3 |
| 1859 | 107933.484 |
| 1860 | 142895.77 |
| 1861 | 109992.336 |
| 1862 | 310831.3 |
| 1863 | 299255.28 |
| 1864 | 299268.8 |
| 1865 | 343841.62 |
| 1866 | 326482.66 |
| 1867 | 227782.98 |
| 1868 | 291853.75 |
| 1869 | 217277.64 |
| 1870 | 228102.27 |
| 1871 | 262453.16 |
| 1872 | 187227.3 |
| 1873 | 250864.22 |
| 1874 | 145362.61 |
| 1875 | 194309.62 |
| 1876 | 201614.14 |
| 1877 | 207402.64 |
| 1878 | 204440.56 |
| 1879 | 124960.95 |
| 1880 | 126347.76 |
| 1881 | 250471.27 |
| 1882 | 241791.14 |
| 1883 | 186584.39 |
| 1884 | 197893.94 |
| 1885 | 226397.67 |
| 1886 | 278702.28 |
| 1887 | 224751.4 |
| 1888 | 265969.9 |
| 1889 | 179244.95 |
| 1890 | 110452.34 |
| 1891 | 120848.664 |
| 1892 | 94345.05 |
| 1893 | 121273.2 |
| 1894 | 117598.22 |
| 1895 | 135010.39 |
| 1896 | 118037.98 |
| 1897 | 117422.47 |
| 1898 | 107270.64 |
| 1899 | 160116.3 |
| 1900 | 157429.16 |
| 1901 | 177027.53 |
| 1902 | 156245.47 |
| 1903 | 221259.45 |
| 1904 | 151770.31 |
| 1905 | 203024.02 |
| 1906 | 161040.6 |
| 1907 | 215120.16 |
| 1908 | 107656.734 |
| 1909 | 137318.7 |
| 1910 | 121638.766 |
| 1911 | 218927.34 |
| 1912 | 306107.16 |
| 1913 | 179769.19 |
| 1914 | 50562.766 |
| 1915 | 314186.1 |
| 1916 | 38800.64 |
| 1917 | 242084.83 |
| 1918 | 136770.16 |
| 1919 | 170342.33 |
| 1920 | 163701.25 |
| 1921 | 365463.2 |
| 1922 | 320650.4 |
| 1923 | 232383.84 |
| 1924 | 237394.1 |
| 1925 | 214693.89 |
| 1926 | 363536.03 |
| 1927 | 123827.24 |
| 1928 | 171968.55 |
| 1929 | 113323.67 |
| 1930 | 119855.7 |
| 1931 | 136828.95 |
| 1932 | 131686.03 |
| 1933 | 192087.19 |
| 1934 | 186589.31 |
| 1935 | 173983.94 |
| 1936 | 198030.95 |
| 1937 | 180854.11 |
| 1938 | 172292.61 |
| 1939 | 247588.83 |
| 1940 | 192262.12 |
| 1941 | 169245.11 |
| 1942 | 169366.89 |
| 1943 | 218114.98 |
| 1944 | 341042.06 |
| 1945 | 359764.78 |
| 1946 | 136147.56 |
| 1947 | 285367.66 |
| 1948 | 176874.7 |
| 1949 | 245946.83 |
| 1950 | 195159.33 |
| 1951 | 249447.81 |
| 1952 | 209365.69 |
| 1953 | 185571.4 |
| 1954 | 188566.03 |
| 1955 | 129424.836 |
| 1956 | 290810.72 |
| 1957 | 158060.36 |
| 1958 | 276487.12 |
| 1959 | 138741.22 |
| 1960 | 86343.63 |
| 1961 | 125915.734 |
| 1962 | 94562.96 |
| 1963 | 110964.164 |
| 1964 | 104556.34 |
| 1965 | 135642.03 |
| 1966 | 132439.56 |
| 1967 | 302895.75 |
| 1968 | 390721.62 |
| 1969 | 360400.16 |
| 1970 | 377830 |
| 1971 | 423149.1 |
| 1972 | 364671.12 |
| 1973 | 290348.3 |
| 1974 | 327714.38 |
| 1975 | 444677.72 |
| 1976 | 286352.62 |
| 1977 | 355486.9 |
| 1978 | 328790.62 |
| 1979 | 318982.03 |
| 1980 | 197991.42 |
| 1981 | 341432.03 |
| 1982 | 228534.23 |
| 1983 | 212599.06 |
| 1984 | 181306.8 |
| 1985 | 232146.98 |
| 1986 | 213441.06 |
| 1987 | 192692.75 |
| 1988 | 184191.58 |
| 1989 | 201366.88 |
| 1990 | 217518.03 |
| 1991 | 236490.97 |
| 1992 | 233318.23 |
| 1993 | 177581.44 |
| 1994 | 225120.64 |
| 1995 | 189313.48 |
| 1996 | 282999.97 |
| 1997 | 303970.97 |
| 1998 | 305415.78 |
| 1999 | 295546 |
| 2000 | 303979.88 |
| 2001 | 291034.28 |
| 2002 | 249561.94 |
| 2003 | 260253.61 |
| 2004 | 295601.25 |
| 2005 | 231685.67 |
| 2006 | 218293.47 |
| 2007 | 251289.33 |
| 2008 | 229620.78 |
| 2009 | 208053.84 |
| 2010 | 197810.36 |
| 2011 | 136664.83 |
| 2012 | 179707.7 |
| 2013 | 177737.77 |
| 2014 | 190983.55 |
| 2015 | 208944.69 |
| 2016 | 198256.69 |
| 2017 | 201419.83 |
| 2018 | 113525.91 |
| 2019 | 130375.17 |
| 2020 | 78022.016 |
| 2021 | 88089.164 |
| 2022 | 204469.31 |
| 2023 | 134270.03 |
| 2024 | 279730.1 |
| 2025 | 344480.8 |
| 2026 | 173909 |
| 2027 | 161354.03 |
| 2028 | 155323.4 |
| 2029 | 169542.48 |
| 2030 | 261390.88 |
| 2031 | 237724.33 |
| 2032 | 251362.9 |
| 2033 | 245380.56 |
| 2034 | 171309.39 |
| 2035 | 235745.61 |
| 2036 | 211420.66 |
| 2037 | 212782.61 |
| 2038 | 298426.25 |
| 2039 | 229864.08 |
| 2040 | 316692.03 |
| 2041 | 290950.4 |
| 2042 | 210255.33 |
| 2043 | 181058.2 |
| 2044 | 177827.66 |
| 2045 | 202248.98 |
| 2046 | 129544.15 |
| 2047 | 136158.52 |
| 2048 | 149633.92 |
| 2049 | 139975.11 |
| 2050 | 163222.98 |
| 2051 | 107814.52 |
| 2052 | 114985.27 |
| 2053 | 145502.86 |
| 2054 | 77206.83 |
| 2055 | 163909.06 |
| 2056 | 140477.45 |
| 2057 | 99820.53 |
| 2058 | 225086.83 |
| 2059 | 130412.16 |
| 2060 | 185165.69 |
| 2061 | 172888.33 |
| 2062 | 115274.61 |
| 2063 | 108105.77 |
| 2064 | 139543.58 |
| 2065 | 118941.98 |
| 2066 | 176248.66 |
| 2067 | 127431.64 |
| 2068 | 143541.88 |
| 2069 | 83313.2 |
| 2070 | 105030.2 |
| 2071 | 97115.02 |
| 2072 | 165747.39 |
| 2073 | 122868.086 |
| 2074 | 182773.69 |
| 2075 | 153989.22 |
| 2076 | 126447.09 |
| 2077 | 149467.39 |
| 2078 | 118796.3 |
| 2079 | 136468.56 |
| 2080 | 109687.945 |
| 2081 | 114276.14 |
| 2082 | 130087.55 |
| 2083 | 148315.88 |
| 2084 | 102425.28 |
| 2085 | 96556.72 |
| 2086 | 117271.17 |
| 2087 | 116443.55 |
| 2088 | 102453.48 |
| 2089 | 67236.79 |
| 2090 | 127293.07 |
| 2091 | 95903.83 |
| 2092 | 145303.52 |
| 2093 | 133460.1 |
| 2094 | 117623.69 |
| 2095 | 144513.61 |
| 2096 | 79454.63 |
| 2097 | 96299.266 |
| 2098 | 149284.69 |
| 2099 | 36690.09 |
| 2100 | 60520.203 |
| 2101 | 124880.086 |
| 2102 | 127649.29 |
| 2103 | 92314.79 |
| 2104 | 128594.72 |
| 2105 | 142510.14 |
| 2106 | 42127.43 |
| 2107 | 206018.81 |
| 2108 | 114330.36 |
| 2109 | 102441.72 |
| 2110 | 124475.305 |
| 2111 | 139695.6 |
| 2112 | 139182.97 |
| 2113 | 106880.31 |
| 2114 | 113849.64 |
| 2115 | 157879.84 |
| 2116 | 124394.836 |
| 2117 | 156753.14 |
| 2118 | 120575.14 |
| 2119 | 114321.83 |
| 2120 | 119997.695 |
| 2121 | 99331.02 |
| 2122 | 116062.33 |
| 2123 | 86642.61 |
| 2124 | 170669.8 |
| 2125 | 137863.75 |
| 2126 | 164155.19 |
| 2127 | 176637.75 |
| 2128 | 130764.555 |
| 2129 | 80336.766 |
| 2130 | 129541.195 |
| 2131 | 145423.12 |
| 2132 | 119677.92 |
| 2133 | 126364.08 |
| 2134 | 123006.836 |
| 2135 | 98555.91 |
| 2136 | 56821.473 |
| 2137 | 107099.24 |
| 2138 | 126593.484 |
| 2139 | 142356.4 |
| 2140 | 140556.97 |
| 2141 | 156097.16 |
| 2142 | 123267.49 |
| 2143 | 156064.64 |
| 2144 | 106580.125 |
| 2145 | 141462.39 |
| 2146 | 183934.48 |
| 2147 | 153289.62 |
| 2148 | 137080.89 |
| 2149 | 146522.52 |
| 2150 | 239545.02 |
| 2151 | 116911.35 |
| 2152 | 179186.25 |
| 2153 | 189603.12 |
| 2154 | 104734.984 |
| 2155 | 138008.84 |
| 2156 | 247315.38 |
| 2157 | 240962.92 |
| 2158 | 237414.61 |
| 2159 | 216123.8 |
| 2160 | 198969.9 |
| 2161 | 242800.92 |
| 2162 | 372399.62 |
| 2163 | 347945.56 |
| 2164 | 247858.81 |
| 2165 | 205804.66 |
| 2166 | 161899.55 |
| 2167 | 216748.14 |
| 2168 | 184269.84 |
| 2169 | 194392.2 |
| 2170 | 213005.47 |
| 2171 | 154057.2 |
| 2172 | 138397.52 |
| 2173 | 184006.66 |
| 2174 | 220972.17 |
| 2175 | 282537.7 |
| 2176 | 298441.75 |
| 2177 | 239556.61 |
| 2178 | 218199.12 |
| 2179 | 135466.19 |
| 2180 | 218276.03 |
| 2181 | 194842.19 |
| 2182 | 222855.89 |
| 2183 | 193087.56 |
| 2184 | 121309.84 |
| 2185 | 118380.055 |
| 2186 | 157250.95 |
| 2187 | 153284.58 |
| 2188 | 162235.88 |
| 2189 | 300597.38 |
| 2190 | 72580.46 |
| 2191 | 60497.64 |
| 2192 | 80304.18 |
| 2193 | 119989.63 |
| 2194 | 116577.61 |
| 2195 | 88022.945 |
| 2196 | 92677.11 |
| 2197 | 115559.875 |
| 2198 | 169024.36 |
| 2199 | 192694.97 |
| 2200 | 151424.89 |
| 2201 | 149350.88 |
| 2202 | 194655.25 |
| 2203 | 146507.19 |
| 2204 | 168743.45 |
| 2205 | 109194.9 |
| 2206 | 150341.62 |
| 2207 | 226740.1 |
| 2208 | 255365.88 |
| 2209 | 246391.88 |
| 2210 | 119880.42 |
| 2211 | 121254.31 |
| 2212 | 115540.97 |
| 2213 | 102907.47 |
| 2214 | 136083.2 |
| 2215 | 97332.27 |
| 2216 | 144277.47 |
| 2217 | 60716.445 |
| 2218 | 62763.176 |
| 2219 | 63627.38 |
| 2220 | 44845.117 |
| 2221 | 315890.84 |
| 2222 | 290799.25 |
| 2223 | 298718.16 |
| 2224 | 222589.5 |
| 2225 | 125323.4 |
| 2226 | 186432.38 |
| 2227 | 212397.86 |
| 2228 | 287098.34 |
| 2229 | 254628.03 |
| 2230 | 152998.44 |
| 2231 | 222075.47 |
| 2232 | 191789.6 |
| 2233 | 187031.58 |
| 2234 | 257058.23 |
| 2235 | 230272.05 |
| 2236 | 258999.98 |
| 2237 | 319799.84 |
| 2238 | 214048.78 |
| 2239 | 102065.09 |
| 2240 | 158464.89 |
| 2241 | 137169.53 |
| 2242 | 124611.5 |
| 2243 | 124103.25 |
| 2244 | 98728.26 |
| 2245 | 97152.586 |
| 2246 | 123724.586 |
| 2247 | 140450.61 |
| 2248 | 121787.1 |
| 2249 | 111147.11 |
| 2250 | 120888.19 |
| 2251 | 101792.74 |
| 2252 | 198713.98 |
| 2253 | 161833.39 |
| 2254 | 178705.89 |
| 2255 | 195938.16 |
| 2256 | 170568.7 |
| 2257 | 207306.77 |
| 2258 | 148824.89 |
| 2259 | 179240.61 |
| 2260 | 145916.64 |
| 2261 | 204387.14 |
| 2262 | 213312.02 |
| 2263 | 356149.7 |
| 2264 | 424961.84 |
| 2265 | 164165.1 |
| 2266 | 289722.34 |
| 2267 | 358621.78 |
| 2268 | 381879.7 |
| 2269 | 159660 |
| 2270 | 195292.52 |
| 2271 | 212519.67 |
| 2272 | 210709.94 |
| 2273 | 154529.36 |
| 2274 | 187911.89 |
| 2275 | 173502.78 |
| 2276 | 185015.67 |
| 2277 | 182418.69 |
| 2278 | 155445.45 |
| 2279 | 118111.375 |
| 2280 | 99937.516 |
| 2281 | 170798.92 |
| 2282 | 184701.4 |
| 2283 | 112071.48 |
| 2284 | 111875.59 |
| 2285 | 136035.3 |
| 2286 | 117776.555 |
| 2287 | 353495.8 |
| 2288 | 288167.7 |
| 2289 | 338394.9 |
| 2290 | 401648.4 |
| 2291 | 331627.44 |
| 2292 | 395713.53 |
| 2293 | 420412.84 |
| 2294 | 371483.97 |
| 2295 | 443061.25 |
| 2296 | 268960.22 |
| 2297 | 349099.84 |
| 2298 | 348978.34 |
| 2299 | 346810.2 |
| 2300 | 317753.56 |
| 2301 | 323764.47 |
| 2302 | 258243.17 |
| 2303 | 246624.14 |
| 2304 | 254756.1 |
| 2305 | 208520.3 |
| 2306 | 200543.64 |
| 2307 | 213548.14 |
| 2308 | 225429.28 |
| 2309 | 290402.88 |
| 2310 | 224727.7 |
| 2311 | 220170.33 |
| 2312 | 186990.95 |
| 2313 | 172943.11 |
| 2314 | 176099.8 |
| 2315 | 188014.77 |
| 2316 | 207944.2 |
| 2317 | 190642.86 |
| 2318 | 185961.94 |
| 2319 | 189284.98 |
| 2320 | 178989.8 |
| 2321 | 242906.52 |
| 2322 | 196483.64 |
| 2323 | 193020.61 |
| 2324 | 195400.62 |
| 2325 | 216134.6 |
| 2326 | 182904.67 |
| 2327 | 201725.58 |
| 2328 | 226895.67 |
| 2329 | 192693.9 |
| 2330 | 187529.69 |
| 2331 | 333384.44 |
| 2332 | 357222.97 |
| 2333 | 306101.4 |
| 2334 | 259598.67 |
| 2335 | 281031.22 |
| 2336 | 300657.84 |
| 2337 | 192688.86 |
| 2338 | 257907.2 |
| 2339 | 227978.97 |
| 2340 | 383653.2 |
| 2341 | 223894.42 |
| 2342 | 233720.42 |
| 2343 | 236350.77 |
| 2344 | 218003.81 |
| 2345 | 234511.58 |
| 2346 | 212130.2 |
| 2347 | 197132.56 |
| 2348 | 247031.4 |
| 2349 | 195420.42 |
| 2350 | 315577.03 |
| 2351 | 260189.48 |
| 2352 | 248716.33 |
| 2353 | 254267.08 |
| 2354 | 149484.08 |
| 2355 | 149366.16 |
| 2356 | 149691.28 |
| 2357 | 194267.88 |
| 2358 | 193633.06 |
| 2359 | 126845.055 |
| 2360 | 108403.15 |
| 2361 | 157055.08 |
| 2362 | 254361.95 |
| 2363 | 133196.9 |
| 2364 | 175922.94 |
| 2365 | 222858.67 |
| 2366 | 197914.94 |
| 2367 | 214889.56 |
| 2368 | 218312.94 |
| 2369 | 214715.7 |
| 2370 | 173079.19 |
| 2371 | 159399.66 |
| 2372 | 190049.03 |
| 2373 | 290456.12 |
| 2374 | 309481.44 |
| 2375 | 248736.11 |
| 2376 | 297857.22 |
| 2377 | 320124.06 |
| 2378 | 143417.44 |
| 2379 | 213944.84 |
| 2380 | 141978.1 |
| 2381 | 174467.8 |
| 2382 | 216474.55 |
| 2383 | 195846.11 |
| 2384 | 244924.88 |
| 2385 | 164095.55 |
| 2386 | 121780.27 |
| 2387 | 119279.25 |
| 2388 | 112594.83 |
| 2389 | 122109.19 |
| 2390 | 151334.38 |
| 2391 | 144134.4 |
| 2392 | 112780.625 |
| 2393 | 175823.5 |
| 2394 | 142334.38 |
| 2395 | 216090.64 |
| 2396 | 137460.3 |
| 2397 | 213911.67 |
| 2398 | 139653.61 |
| 2399 | 64441.945 |
| 2400 | 63638.02 |
| 2401 | 121158.28 |
| 2402 | 141936.4 |
| 2403 | 145107.75 |
| 2404 | 157222.94 |
| 2405 | 167211.2 |
| 2406 | 138359.61 |
| 2407 | 121546.3 |
| 2408 | 142174.28 |
| 2409 | 105895.96 |
| 2410 | 180068.67 |
| 2411 | 109893.234 |
| 2412 | 151322.66 |
| 2413 | 119768.125 |
| 2414 | 158800.58 |
| 2415 | 135627.98 |
| 2416 | 126582.36 |
| 2417 | 138839.05 |
| 2418 | 131610.03 |
| 2419 | 121987.13 |
| 2420 | 122637.96 |
| 2421 | 132496.44 |
| 2422 | 101419.58 |
| 2423 | 132090.5 |
| 2424 | 155953.38 |
| 2425 | 234068 |
| 2426 | 157920.72 |
| 2427 | 132363.14 |
| 2428 | 197263.84 |
| 2429 | 96575.97 |
| 2430 | 127218.88 |
| 2431 | 102561.63 |
| 2432 | 150606.75 |
| 2433 | 152024.83 |
| 2434 | 142579.98 |
| 2435 | 164310.14 |
| 2436 | 105742.39 |
| 2437 | 87084.22 |
| 2438 | 112235.22 |
| 2439 | 106183.83 |
| 2440 | 127022.37 |
| 2441 | 104680.94 |
| 2442 | 94290.41 |
| 2443 | 142541.47 |
| 2444 | 136019.45 |
| 2445 | 81525.99 |
| 2446 | 143845.4 |
| 2447 | 212452.39 |
| 2448 | 139668.45 |
| 2449 | 117009.1 |
| 2450 | 158053.67 |
| 2451 | 128273.4 |
| 2452 | 203316.9 |
| 2453 | 87981.125 |
| 2454 | 125068 |
| 2455 | 145942.38 |
| 2456 | 133061.78 |
| 2457 | 137796.1 |
| 2458 | 135664.55 |
| 2459 | 115650.36 |
| 2460 | 159323.52 |
| 2461 | 126426.85 |
| 2462 | 134114.39 |
| 2463 | 129103.63 |
| 2464 | 185009.62 |
| 2465 | 140319.31 |
| 2466 | 115379.695 |
| 2467 | 147227.53 |
| 2468 | 94233.48 |
| 2469 | 82320.65 |
| 2470 | 205620.12 |
| 2471 | 213453.47 |
| 2472 | 170324.97 |
| 2473 | 107433.74 |
| 2474 | 57644.57 |
| 2475 | 218314.89 |
| 2476 | 97317.97 |
| 2477 | 107090.484 |
| 2478 | 151249.55 |
| 2479 | 92348.75 |
| 2480 | 159604.58 |
| 2481 | 124259.016 |
| 2482 | 115308.34 |
| 2483 | 94476.89 |
| 2484 | 132420.27 |
| 2485 | 117582.89 |
| 2486 | 155551.9 |
| 2487 | 207302.52 |
| 2488 | 177627.22 |
| 2489 | 159450.67 |
| 2490 | 138633.14 |
| 2491 | 97022.87 |
| 2492 | 197976.7 |
| 2493 | 162447.27 |
| 2494 | 150426.5 |
| 2495 | 69021.05 |
| 2496 | 239681.11 |
| 2497 | 151964.94 |
| 2498 | 109070.07 |
| 2499 | 83445.055 |
| 2500 | 118828.17 |
| 2501 | 131021.945 |
| 2502 | 150892.19 |
| 2503 | 102408.83 |
| 2504 | 182420.45 |
| 2505 | 224363.69 |
| 2506 | 263016.66 |
| 2507 | 289070.72 |
| 2508 | 260050.22 |
| 2509 | 224900.55 |
| 2510 | 219527.48 |
| 2511 | 177975.53 |
| 2512 | 209029.47 |
| 2513 | 229764.78 |
| 2514 | 253553.27 |
| 2515 | 151045.73 |
| 2516 | 180712.31 |
| 2517 | 148802.92 |
| 2518 | 154810.17 |
| 2519 | 236933.77 |
| 2520 | 222842 |
| 2521 | 189206.64 |
| 2522 | 226648.27 |
| 2523 | 106986.61 |
| 2524 | 136700.52 |
| 2525 | 143917.73 |
| 2526 | 149995.61 |
| 2527 | 106666.8 |
| 2528 | 121268.29 |
| 2529 | 147701.78 |
| 2530 | 122811.99 |
| 2531 | 253765.33 |
| 2532 | 225002.58 |
| 2533 | 205715.58 |
| 2534 | 243815.28 |
| 2535 | 271513.1 |
| 2536 | 226802.92 |
| 2537 | 243578.23 |
| 2538 | 192006.38 |
| 2539 | 192681.19 |
| 2540 | 188746.53 |
| 2541 | 186771.11 |
| 2542 | 167397.25 |
| 2543 | 114243.27 |
| 2544 | 108207.18 |
| 2545 | 138550.05 |
| 2546 | 128880.4 |
| 2547 | 153440.98 |
| 2548 | 166619.3 |
| 2549 | 170107.77 |
| 2550 | 632049.94 |
| 2551 | 136753 |
| 2552 | 136638.28 |
| 2553 | 56785.57 |
| 2554 | 87176.836 |
| 2555 | 113592.4 |
| 2556 | 85733.1 |
| 2557 | 97557.71 |
| 2558 | 175308.58 |
| 2559 | 135328.47 |
| 2560 | 175455.47 |
| 2561 | 154635.75 |
| 2562 | 149361.19 |
| 2563 | 147614.55 |
| 2564 | 202234.88 |
| 2565 | 174037.36 |
| 2566 | 164823.28 |
| 2567 | 133644.38 |
| 2568 | 228825 |
| 2569 | 234001.47 |
| 2570 | 114675.64 |
| 2571 | 189627.22 |
| 2572 | 154509.77 |
| 2573 | 226698.14 |
| 2574 | 265826 |
| 2575 | 136712.9 |
| 2576 | 137318.16 |
| 2577 | 164742.97 |
| 2578 | 68704.36 |
| 2579 | 36073.35 |
| 2580 | 100195.695 |
| 2581 | 132664.42 |
| 2582 | 128382.836 |
| 2583 | 290881 |
| 2584 | 177855.16 |
| 2585 | 200544.55 |
| 2586 | 220444.58 |
| 2587 | 208417.22 |
| 2588 | 141271.05 |
| 2589 | 145599.78 |
| 2590 | 223740.7 |
| 2591 | 253441.28 |
| 2592 | 221227.72 |
| 2593 | 271671.06 |
| 2594 | 177183.31 |
| 2595 | 216799.66 |
| 2596 | 310295.6 |
| 2597 | 206036.39 |
| 2598 | 283113.5 |
| 2599 | 335723.38 |
| 2600 | 175327.52 |
| 2601 | 142256.89 |
| 2602 | 67697.53 |
| 2603 | 85908.83 |
| 2604 | 85334.5 |
| 2605 | 63122.656 |
| 2606 | 140956.44 |
| 2607 | 237205.98 |
| 2608 | 205817.58 |
| 2609 | 169601.98 |
| 2610 | 109925.13 |
| 2611 | 125129.57 |
| 2612 | 160685.05 |
| 2613 | 124423.266 |
| 2614 | 106642.734 |
| 2615 | 164238.94 |
| 2616 | 163467.12 |
| 2617 | 207489.14 |
| 2618 | 243113.23 |
| 2619 | 215920.45 |
| 2620 | 199205.5 |
| 2621 | 175588.02 |
| 2622 | 186382.38 |
| 2623 | 232988.58 |
| 2624 | 304002.75 |
| 2625 | 271988.12 |
| 2626 | 177953.9 |
| 2627 | 165756.03 |
| 2628 | 423319.97 |
| 2629 | 442661.8 |
| 2630 | 356875.16 |
| 2631 | 418986.9 |
| 2632 | 384186.6 |
| 2633 | 296088.06 |
| 2634 | 389720.03 |
| 2635 | 151187.3 |
| 2636 | 175498.06 |
| 2637 | 196005.14 |
| 2638 | 263965.53 |
| 2639 | 181826.62 |
| 2640 | 154998.8 |
| 2641 | 100981.68 |
| 2642 | 186425.42 |
| 2643 | 115201.24 |
| 2644 | 115152.695 |
| 2645 | 107302.87 |
| 2646 | 94237.56 |
| 2647 | 108397.9 |
| 2648 | 134320.2 |
| 2649 | 150222.11 |
| 2650 | 124908.11 |
| 2651 | 134481.92 |
| 2652 | 368143.34 |
| 2653 | 257552.64 |
| 2654 | 267735.16 |
| 2655 | 389236.1 |
| 2656 | 329237.12 |
| 2657 | 341846.6 |
| 2658 | 311920.12 |
| 2659 | 311724.7 |
| 2660 | 352734.47 |
| 2661 | 341331.06 |
| 2662 | 361729.47 |
| 2663 | 284668.28 |
| 2664 | 281643.94 |
| 2665 | 338483.3 |
| 2666 | 293442.34 |
| 2667 | 185647.17 |
| 2668 | 188634.44 |
| 2669 | 188881.62 |
| 2670 | 273139.34 |
| 2671 | 198024.66 |
| 2672 | 203083.78 |
| 2673 | 198801.03 |
| 2674 | 201874.75 |
| 2675 | 182893.9 |
| 2676 | 200920.94 |
| 2677 | 202844.25 |
| 2678 | 243786.44 |
| 2679 | 287026.38 |
| 2680 | 281090.38 |
| 2681 | 375324.44 |
| 2682 | 312524.2 |
| 2683 | 452200.62 |
| 2684 | 307911.8 |
| 2685 | 317881.06 |
| 2686 | 264242.66 |
| 2687 | 302704.84 |
| 2688 | 211291.66 |
| 2689 | 208083.3 |
| 2690 | 363873.6 |
| 2691 | 190423.53 |
| 2692 | 151636.83 |
| 2693 | 205895.75 |
| 2694 | 138873.72 |
| 2695 | 204161.86 |
| 2696 | 188665.86 |
| 2697 | 189169.81 |
| 2698 | 206106.16 |
| 2699 | 167810.44 |
| 2700 | 146637.77 |
| 2701 | 149884.67 |
| 2702 | 111451.586 |
| 2703 | 125808.8 |
| 2704 | 151840.12 |
| 2705 | 104957.18 |
| 2706 | 82167.07 |
| 2707 | 121665.836 |
| 2708 | 130133.78 |
| 2709 | 111813.57 |
| 2710 | 125930.42 |
| 2711 | 286431.22 |
| 2712 | 379128.47 |
| 2713 | 169412.22 |
| 2714 | 145548.45 |
| 2715 | 177203.45 |
| 2716 | 144775.69 |
| 2717 | 192737.33 |
| 2718 | 214468.48 |
| 2719 | 142167.05 |
| 2720 | 187678.3 |
| 2721 | 122154.7 |
| 2722 | 155253.38 |
| 2723 | 146853.11 |
| 2724 | 113770.484 |
| 2725 | 120849.76 |
| 2726 | 140590.27 |
| 2727 | 178932.89 |
| 2728 | 192774.55 |
| 2729 | 146546.5 |
| 2730 | 142032 |
| 2731 | 130415.625 |
| 2732 | 137039.8 |
| 2733 | 169931.19 |
| 2734 | 144169.06 |
| 2735 | 131644.69 |
| 2736 | 140667.9 |
| 2737 | 117505.98 |
| 2738 | 126876.47 |
| 2739 | 156556.42 |
| 2740 | 144806.52 |
| 2741 | 138315.12 |
| 2742 | 172950.81 |
| 2743 | 154055.39 |
| 2744 | 169012.78 |
| 2745 | 147130.81 |
| 2746 | 133334.94 |
| 2747 | 158898.8 |
| 2748 | 114636.55 |
| 2749 | 135266.58 |
| 2750 | 115382.64 |
| 2751 | 135356.56 |
| 2752 | 217939.88 |
| 2753 | 164413.17 |
| 2754 | 260829.58 |
| 2755 | 142499.69 |
| 2756 | 90671.46 |
| 2757 | 70959 |
| 2758 | 90794.875 |
| 2759 | 172922.94 |
| 2760 | 130547.664 |
| 2761 | 146075.47 |
| 2762 | 127897.445 |
| 2763 | 195832.22 |
| 2764 | 156677.05 |
| 2765 | 286615.97 |
| 2766 | 118918.51 |
| 2767 | 83088.51 |
| 2768 | 123890.21 |
| 2769 | 137663.25 |
| 2770 | 145482.55 |
| 2771 | 96845.75 |
| 2772 | 104116.57 |
| 2773 | 180693.47 |
| 2774 | 139519.48 |
| 2775 | 122477.13 |
| 2776 | 146383.88 |
| 2777 | 157243.62 |
| 2778 | 114620.51 |
| 2779 | 121435.17 |
| 2780 | 93864.81 |
| 2781 | 80680.516 |
| 2782 | 80079.45 |
| 2783 | 91807.33 |
| 2784 | 127609.72 |
| 2785 | 141444.27 |
| 2786 | 53422.36 |
| 2787 | 119806.51 |
| 2788 | 61782.207 |
| 2789 | 175729.34 |
| 2790 | 105167.016 |
| 2791 | 107341.74 |
| 2792 | 59601.79 |
| 2793 | 160198.78 |
| 2794 | 93006.75 |
| 2795 | 117950.1 |
| 2796 | 97954.26 |
| 2797 | 195539.88 |
| 2798 | 118966.53 |
| 2799 | 109352.92 |
| 2800 | 68499.414 |
| 2801 | 104069.13 |
| 2802 | 120118.766 |
| 2803 | 158139.36 |
| 2804 | 136711.8 |
| 2805 | 110068.445 |
| 2806 | 66323.52 |
| 2807 | 166659.55 |
| 2808 | 164967.42 |
| 2809 | 118846.8 |
| 2810 | 119979.68 |
| 2811 | 184912.52 |
| 2812 | 181788.11 |
| 2813 | 153442.02 |
| 2814 | 148336.8 |
| 2815 | 114209.875 |
| 2816 | 227653.08 |
| 2817 | 169597.78 |
| 2818 | 124307.695 |
| 2819 | 194838.02 |
| 2820 | 139595.95 |
| 2821 | 120197.086 |
| 2822 | 190252.94 |
| 2823 | 308789.75 |
| 2824 | 179535.75 |
| 2825 | 176111.73 |
| 2826 | 136909.27 |
| 2827 | 130162.99 |
| 2828 | 228956.16 |
| 2829 | 227076.52 |
| 2830 | 237156.56 |
| 2831 | 193822.38 |
| 2832 | 241089.47 |
| 2833 | 304543.7 |
| 2834 | 227301.06 |
| 2835 | 229116.36 |
| 2836 | 205684.11 |
| 2837 | 159602.02 |
| 2838 | 140022.38 |
| 2839 | 172519.83 |
| 2840 | 204046.6 |
| 2841 | 204397.58 |
| 2842 | 233186.67 |
| 2843 | 148495.98 |
| 2844 | 184657.23 |
| 2845 | 119342.414 |
| 2846 | 213416.17 |
| 2847 | 217466.17 |
| 2848 | 207878.9 |
| 2849 | 199796.9 |
| 2850 | 276615.72 |
| 2851 | 210204.67 |
| 2852 | 232797.23 |
| 2853 | 234925.92 |
| 2854 | 144556.6 |
| 2855 | 205847.33 |
| 2856 | 206303.03 |
| 2857 | 191376.44 |
| 2858 | 212924.3 |
| 2859 | 92595.84 |
| 2860 | 147669.14 |
| 2861 | 125396.03 |
| 2862 | 210402.7 |
| 2863 | 141268.16 |
| 2864 | 255907.52 |
| 2865 | 139740.16 |
| 2866 | 146773.39 |
| 2867 | 86024.64 |
| 2868 | 111008.71 |
| 2869 | 96480.734 |
| 2870 | 126101.14 |
| 2871 | 83182.734 |
| 2872 | 11204.42 |
| 2873 | 92011.66 |
| 2874 | 144366.08 |
| 2875 | 108190.29 |
| 2876 | 168017.5 |
| 2877 | 141247.52 |
| 2878 | 154234.95 |
| 2879 | 133811.38 |
| 2880 | 91145.42 |
| 2881 | 140921.7 |
| 2882 | 181104.83 |
| 2883 | 200932.38 |
| 2884 | 208622 |
| 2885 | 185701.48 |
| 2886 | 244048.89 |
| 2887 | 105363.88 |
| 2888 | 150092.7 |
| 2889 | 49186.582 |
| 2890 | 73777.49 |
| 2891 | 138551.23 |
| 2892 | 39044.88 |
| 2893 | 75943.32 |
| 2894 | 35523.707 |
| 2895 | 330151.03 |
| 2896 | 289476 |
| 2897 | 215517.52 |
| 2898 | 140754.28 |
| 2899 | 213778.42 |
| 2900 | 166029.47 |
| 2901 | 216113.6 |
| 2902 | 188425.56 |
| 2903 | 318239.38 |
| 2904 | 338552.12 |
| 2905 | 67743 |
| 2906 | 210201.06 |
| 2907 | 108446.34 |
| 2908 | 114567.125 |
| 2909 | 138720.25 |
| 2910 | 69767.32 |
| 2911 | 70828.086 |
| 2912 | 149327.28 |
| 2913 | 66131 |
| 2914 | 65598.44 |
| 2915 | 78043.51 |
| 2916 | 74433.22 |
| 2917 | 182310.4 |
| 2918 | 112793.62 |
| 2919 | 236883.72 |
submission改进版
| Id | SalePrice |
| 1461 | 113816.58 |
| 1462 | 158432.16 |
| 1463 | 182454.11 |
| 1464 | 192929.03 |
| 1465 | 190422.6 |
| 1466 | 172855.08 |
| 1467 | 175751.14 |
| 1468 | 163481.38 |
| 1469 | 193167.3 |
| 1470 | 126402.25 |
| 1471 | 172077.23 |
| 1472 | 100014.164 |
| 1473 | 95924.97 |
| 1474 | 147253.47 |
| 1475 | 112133.08 |
| 1476 | 360062.84 |
| 1477 | 253665.28 |
| 1478 | 308819.44 |
| 1479 | 307205.7 |
| 1480 | 468440.1 |
| 1481 | 321691.5 |
| 1482 | 211007.66 |
| 1483 | 174627.39 |
| 1484 | 167452.81 |
| 1485 | 192062.83 |
| 1486 | 192640.17 |
| 1487 | 340076.53 |
| 1488 | 242860.08 |
| 1489 | 190053.6 |
| 1490 | 248150.97 |
| 1491 | 197189.33 |
| 1492 | 96830.69 |
| 1493 | 208703 |
| 1494 | 297678.34 |
| 1495 | 283630.06 |
| 1496 | 252711.9 |
| 1497 | 178221.11 |
| 1498 | 172065.66 |
| 1499 | 166413.56 |
| 1500 | 161685.81 |
| 1501 | 186395.75 |
| 1502 | 156482.38 |
| 1503 | 295578.56 |
| 1504 | 243695.92 |
| 1505 | 223383.28 |
| 1506 | 190228.94 |
| 1507 | 247864.77 |
| 1508 | 196947.73 |
| 1509 | 165784.31 |
| 1510 | 148379.52 |
| 1511 | 153885.97 |
| 1512 | 170884.84 |
| 1513 | 153683.28 |
| 1514 | 150424.06 |
| 1515 | 192902.58 |
| 1516 | 152284.06 |
| 1517 | 169888.06 |
| 1518 | 130022.69 |
| 1519 | 218552.34 |
| 1520 | 129843.734 |
| 1521 | 136471.42 |
| 1522 | 173864.75 |
| 1523 | 115115.64 |
| 1524 | 127944.38 |
| 1525 | 125068.88 |
| 1526 | 116877.484 |
| 1527 | 108622.05 |
| 1528 | 135576.56 |
| 1529 | 158113.73 |
| 1530 | 212400.77 |
| 1531 | 119006.08 |
| 1532 | 99445.04 |
| 1533 | 150025.28 |
| 1534 | 127187.18 |
| 1535 | 142190.25 |
| 1536 | 104757.31 |
| 1537 | 42281.137 |
| 1538 | 171003.45 |
| 1539 | 228963.28 |
| 1540 | 107250.85 |
| 1541 | 141252.05 |
| 1542 | 142563.36 |
| 1543 | 186393.72 |
| 1544 | 88139.15 |
| 1545 | 121677.12 |
| 1546 | 140944.77 |
| 1547 | 128116.05 |
| 1548 | 145441.28 |
| 1549 | 124092.664 |
| 1550 | 140091.7 |
| 1551 | 114243.33 |
| 1552 | 149666.22 |
| 1553 | 144947.08 |
| 1554 | 124737.2 |
| 1555 | 164717.94 |
| 1556 | 83980.516 |
| 1557 | 108884.95 |
| 1558 | 111711.51 |
| 1559 | 75388.17 |
| 1560 | 121728.36 |
| 1561 | 129828.51 |
| 1562 | 129982.91 |
| 1563 | 129359.13 |
| 1564 | 160002.42 |
| 1565 | 151295.53 |
| 1566 | 249800.92 |
| 1567 | 79003.83 |
| 1568 | 233570.56 |
| 1569 | 130996.47 |
| 1570 | 143398.6 |
| 1571 | 104842.18 |
| 1572 | 143933.97 |
| 1573 | 234889.92 |
| 1574 | 126394.055 |
| 1575 | 235581.47 |
| 1576 | 272386.1 |
| 1577 | 182267.47 |
| 1578 | 155133.2 |
| 1579 | 139578.56 |
| 1580 | 195053.27 |
| 1581 | 157956.73 |
| 1582 | 133506.27 |
| 1583 | 291060.03 |
| 1584 | 221287.3 |
| 1585 | 140182.31 |
| 1586 | 67177.734 |
| 1587 | 110378.914 |
| 1588 | 164665.02 |
| 1589 | 98476.6 |
| 1590 | 134626.98 |
| 1591 | 90614.87 |
| 1592 | 119465.15 |
| 1593 | 136019.95 |
| 1594 | 134475.67 |
| 1595 | 112631.52 |
| 1596 | 216169.17 |
| 1597 | 193927.72 |
| 1598 | 214222.83 |
| 1599 | 187795.31 |
| 1600 | 174351 |
| 1601 | 59450.594 |
| 1602 | 112882.19 |
| 1603 | 84042.15 |
| 1604 | 284428.6 |
| 1605 | 247776.88 |
| 1606 | 158903.11 |
| 1607 | 166864.88 |
| 1608 | 218288.86 |
| 1609 | 182642.75 |
| 1610 | 155880.52 |
| 1611 | 136896.7 |
| 1612 | 176644.88 |
| 1613 | 162895.92 |
| 1614 | 135514.4 |
| 1615 | 96269.31 |
| 1616 | 78066.4 |
| 1617 | 95095.06 |
| 1618 | 127369.94 |
| 1619 | 146648.55 |
| 1620 | 174000.19 |
| 1621 | 134653.47 |
| 1622 | 150110.19 |
| 1623 | 279836.12 |
| 1624 | 203076.78 |
| 1625 | 125407.83 |
| 1626 | 166642.25 |
| 1627 | 190048.9 |
| 1628 | 289153.6 |
| 1629 | 180103.25 |
| 1630 | 342316.75 |
| 1631 | 220504.14 |
| 1632 | 229783.16 |
| 1633 | 183398.8 |
| 1634 | 187926.25 |
| 1635 | 178533.4 |
| 1636 | 151924.88 |
| 1637 | 187136.52 |
| 1638 | 181673.34 |
| 1639 | 183942.84 |
| 1640 | 240894.6 |
| 1641 | 182532.27 |
| 1642 | 255352.44 |
| 1643 | 212145.98 |
| 1644 | 238555.69 |
| 1645 | 205033.27 |
| 1646 | 164578.72 |
| 1647 | 167636.98 |
| 1648 | 134947.47 |
| 1649 | 145763.39 |
| 1650 | 117650.8 |
| 1651 | 118430.28 |
| 1652 | 104233.945 |
| 1653 | 104988.77 |
| 1654 | 151029.75 |
| 1655 | 135840.58 |
| 1656 | 146376.89 |
| 1657 | 155527.36 |
| 1658 | 152697.47 |
| 1659 | 128023.4 |
| 1660 | 147926.38 |
| 1661 | 421646.3 |
| 1662 | 371647.78 |
| 1663 | 367812.8 |
| 1664 | 449628.47 |
| 1665 | 316008.72 |
| 1666 | 331263.66 |
| 1667 | 357877.47 |
| 1668 | 354535.1 |
| 1669 | 322346.9 |
| 1670 | 354709.06 |
| 1671 | 255427.16 |
| 1672 | 410737.2 |
| 1673 | 306157.5 |
| 1674 | 249025.23 |
| 1675 | 192415.7 |
| 1676 | 196134.03 |
| 1677 | 209192.56 |
| 1678 | 448380.6 |
| 1679 | 385175.8 |
| 1680 | 323507.16 |
| 1681 | 262578.7 |
| 1682 | 321257.7 |
| 1683 | 187064.45 |
| 1684 | 174971.22 |
| 1685 | 175832.78 |
| 1686 | 170483.97 |
| 1687 | 170060.47 |
| 1688 | 188909.45 |
| 1689 | 199014.56 |
| 1690 | 199321.95 |
| 1691 | 191247.11 |
| 1692 | 275479 |
| 1693 | 175150.67 |
| 1694 | 186700.86 |
| 1695 | 174914.84 |
| 1696 | 261204.62 |
| 1697 | 178095.5 |
| 1698 | 340676.47 |
| 1699 | 339922.53 |
| 1700 | 261432.12 |
| 1701 | 272006.94 |
| 1702 | 231502.25 |
| 1703 | 234345.08 |
| 1704 | 274441.38 |
| 1705 | 258274.97 |
| 1706 | 372177.6 |
| 1707 | 219048.2 |
| 1708 | 200837.83 |
| 1709 | 260995.92 |
| 1710 | 220209.72 |
| 1711 | 286981.78 |
| 1712 | 255516.08 |
| 1713 | 278123.66 |
| 1714 | 220333.53 |
| 1715 | 209645.69 |
| 1716 | 177786 |
| 1717 | 177324.19 |
| 1718 | 143072.16 |
| 1719 | 217081.89 |
| 1720 | 243194.8 |
| 1721 | 156665.17 |
| 1722 | 126794.15 |
| 1723 | 156959.27 |
| 1724 | 209271.23 |
| 1725 | 239107.23 |
| 1726 | 186671.1 |
| 1727 | 155954.47 |
| 1728 | 173363.95 |
| 1729 | 172392.33 |
| 1730 | 157552.53 |
| 1731 | 124205.89 |
| 1732 | 131420.28 |
| 1733 | 120077.04 |
| 1734 | 123884.02 |
| 1735 | 127596.195 |
| 1736 | 109564.945 |
| 1737 | 326201.56 |
| 1738 | 268024.3 |
| 1739 | 262767.38 |
| 1740 | 204033.38 |
| 1741 | 182330.75 |
| 1742 | 175954.53 |
| 1743 | 177516.11 |
| 1744 | 343044.97 |
| 1745 | 217477.33 |
| 1746 | 188850.58 |
| 1747 | 214355.38 |
| 1748 | 215919.06 |
| 1749 | 141580.81 |
| 1750 | 130854.21 |
| 1751 | 248179.84 |
| 1752 | 123228.8 |
| 1753 | 150557.83 |
| 1754 | 194241.89 |
| 1755 | 166971.69 |
| 1756 | 137711.62 |
| 1757 | 124894.914 |
| 1758 | 147007.83 |
| 1759 | 159838.16 |
| 1760 | 160256.75 |
| 1761 | 139656.08 |
| 1762 | 187477.11 |
| 1763 | 179899.83 |
| 1764 | 122384.67 |
| 1765 | 170986.81 |
| 1766 | 186970.39 |
| 1767 | 222829.28 |
| 1768 | 146644.1 |
| 1769 | 171115.4 |
| 1770 | 159986.94 |
| 1771 | 126083.48 |
| 1772 | 136690.7 |
| 1773 | 129675.6 |
| 1774 | 142533.9 |
| 1775 | 148963.23 |
| 1776 | 132469.28 |
| 1777 | 120397.734 |
| 1778 | 150190.16 |
| 1779 | 123299.1 |
| 1780 | 170639.55 |
| 1781 | 132196.61 |
| 1782 | 87395.46 |
| 1783 | 145947.55 |
| 1784 | 110232.23 |
| 1785 | 129680.1 |
| 1786 | 155628.66 |
| 1787 | 174866.06 |
| 1788 | 56118 |
| 1789 | 104492 |
| 1790 | 85681.92 |
| 1791 | 194470.22 |
| 1792 | 159630.8 |
| 1793 | 132274.44 |
| 1794 | 170618.16 |
| 1795 | 135174.39 |
| 1796 | 134799.44 |
| 1797 | 109880.31 |
| 1798 | 129185.61 |
| 1799 | 115447.45 |
| 1800 | 139022.61 |
| 1801 | 126720.23 |
| 1802 | 123963.39 |
| 1803 | 157102.27 |
| 1804 | 134550.98 |
| 1805 | 140822.14 |
| 1806 | 123985.96 |
| 1807 | 146238.61 |
| 1808 | 124446.18 |
| 1809 | 134975.34 |
| 1810 | 139430.12 |
| 1811 | 87952.875 |
| 1812 | 102070.29 |
| 1813 | 127777.805 |
| 1814 | 101246.07 |
| 1815 | 50006.984 |
| 1816 | 105415.83 |
| 1817 | 109140.87 |
| 1818 | 157760.39 |
| 1819 | 128615.59 |
| 1820 | 55897.164 |
| 1821 | 107089.875 |
| 1822 | 161574.39 |
| 1823 | 48101.84 |
| 1824 | 137840.44 |
| 1825 | 146580.95 |
| 1826 | 106379.57 |
| 1827 | 109682.55 |
| 1828 | 137078.22 |
| 1829 | 136742.62 |
| 1830 | 148344.7 |
| 1831 | 153929.2 |
| 1832 | 73530.15 |
| 1833 | 157823.08 |
| 1834 | 119896.89 |
| 1835 | 105849.63 |
| 1836 | 127193.17 |
| 1837 | 75264.2 |
| 1838 | 124372.4 |
| 1839 | 111513.86 |
| 1840 | 156625.33 |
| 1841 | 141480.1 |
| 1842 | 97375.59 |
| 1843 | 125998.71 |
| 1844 | 146450.6 |
| 1845 | 147542.14 |
| 1846 | 150473.95 |
| 1847 | 169453.06 |
| 1848 | 49455.902 |
| 1849 | 116357.305 |
| 1850 | 120853.65 |
| 1851 | 148103.12 |
| 1852 | 123855.63 |
| 1853 | 130548.84 |
| 1854 | 162865.69 |
| 1855 | 148629.12 |
| 1856 | 233518.28 |
| 1857 | 134982.56 |
| 1858 | 134108.84 |
| 1859 | 116784.16 |
| 1860 | 140739.94 |
| 1861 | 117962.445 |
| 1862 | 334604.88 |
| 1863 | 315378.8 |
| 1864 | 315394.25 |
| 1865 | 356731.16 |
| 1866 | 343453.66 |
| 1867 | 225210.62 |
| 1868 | 284963.94 |
| 1869 | 210019.94 |
| 1870 | 227854.58 |
| 1871 | 272783 |
| 1872 | 176461.14 |
| 1873 | 248629.7 |
| 1874 | 149395.5 |
| 1875 | 186675.44 |
| 1876 | 199651.61 |
| 1877 | 206616.03 |
| 1878 | 203456.22 |
| 1879 | 136586.47 |
| 1880 | 134425.67 |
| 1881 | 248215.47 |
| 1882 | 235627.84 |
| 1883 | 186074.73 |
| 1884 | 199799.62 |
| 1885 | 226421.22 |
| 1886 | 284435.5 |
| 1887 | 221257.19 |
| 1888 | 270584.97 |
| 1889 | 171393.53 |
| 1890 | 117493.06 |
| 1891 | 126577.66 |
| 1892 | 100930.57 |
| 1893 | 137983.6 |
| 1894 | 123530.49 |
| 1895 | 137550.89 |
| 1896 | 130831.89 |
| 1897 | 117904.81 |
| 1898 | 108495.875 |
| 1899 | 166101.39 |
| 1900 | 160495.86 |
| 1901 | 184778.23 |
| 1902 | 161745.8 |
| 1903 | 222748.33 |
| 1904 | 146912.8 |
| 1905 | 191677.9 |
| 1906 | 156644.9 |
| 1907 | 195271.72 |
| 1908 | 113314.586 |
| 1909 | 138064.83 |
| 1910 | 127989.7 |
| 1911 | 213920.58 |
| 1912 | 321022.12 |
| 1913 | 153562.53 |
| 1914 | 72273.54 |
| 1915 | 331452.34 |
| 1916 | 52068.926 |
| 1917 | 238008.56 |
| 1918 | 143781.11 |
| 1919 | 161125.34 |
| 1920 | 152311.3 |
| 1921 | 369272.72 |
| 1922 | 329470.78 |
| 1923 | 241366.27 |
| 1924 | 218875.44 |
| 1925 | 204128.97 |
| 1926 | 371522.8 |
| 1927 | 132483.22 |
| 1928 | 158230.17 |
| 1929 | 123059.5 |
| 1930 | 127034.85 |
| 1931 | 125186.836 |
| 1932 | 135518.28 |
| 1933 | 185867.61 |
| 1934 | 181834 |
| 1935 | 172029.75 |
| 1936 | 199968.1 |
| 1937 | 181040.34 |
| 1938 | 171487.44 |
| 1939 | 253830.16 |
| 1940 | 189877.28 |
| 1941 | 169020.28 |
| 1942 | 174700.89 |
| 1943 | 228672.31 |
| 1944 | 378843.25 |
| 1945 | 392469.3 |
| 1946 | 129814.94 |
| 1947 | 284670.12 |
| 1948 | 174695.45 |
| 1949 | 253394.2 |
| 1950 | 192195.27 |
| 1951 | 250084.75 |
| 1952 | 206315.64 |
| 1953 | 175459.33 |
| 1954 | 185135.03 |
| 1955 | 141416.14 |
| 1956 | 326049.6 |
| 1957 | 155117.8 |
| 1958 | 285978.8 |
| 1959 | 147326.38 |
| 1960 | 108863.15 |
| 1961 | 126917.914 |
| 1962 | 100565.695 |
| 1963 | 107844.01 |
| 1964 | 111483.54 |
| 1965 | 145817.39 |
| 1966 | 144214.75 |
| 1967 | 306016.16 |
| 1968 | 413894.62 |
| 1969 | 376545.22 |
| 1970 | 398942.34 |
| 1971 | 450446.97 |
| 1972 | 372186.1 |
| 1973 | 298316.72 |
| 1974 | 338782.1 |
| 1975 | 453315.28 |
| 1976 | 292574.44 |
| 1977 | 364004.22 |
| 1978 | 345845.62 |
| 1979 | 323377.53 |
| 1980 | 187148.98 |
| 1981 | 345224.88 |
| 1982 | 218255.6 |
| 1983 | 203554.56 |
| 1984 | 172677.53 |
| 1985 | 238870.61 |
| 1986 | 212535.58 |
| 1987 | 194141.53 |
| 1988 | 174678.06 |
| 1989 | 190827.8 |
| 1990 | 207973.27 |
| 1991 | 226095.48 |
| 1992 | 225426.64 |
| 1993 | 168663.44 |
| 1994 | 225286.02 |
| 1995 | 183634.08 |
| 1996 | 275312.94 |
| 1997 | 322573.8 |
| 1998 | 306569.34 |
| 1999 | 307092.47 |
| 2000 | 328527.8 |
| 2001 | 289683.66 |
| 2002 | 248973.61 |
| 2003 | 261665.08 |
| 2004 | 299097 |
| 2005 | 228268.08 |
| 2006 | 222115.7 |
| 2007 | 253017.11 |
| 2008 | 217522.7 |
| 2009 | 203901.6 |
| 2010 | 193050.39 |
| 2011 | 140304.66 |
| 2012 | 176820.9 |
| 2013 | 181247.34 |
| 2014 | 188746.55 |
| 2015 | 212531.94 |
| 2016 | 194950.33 |
| 2017 | 198835.86 |
| 2018 | 116436.38 |
| 2019 | 132688.55 |
| 2020 | 99979.71 |
| 2021 | 101930.52 |
| 2022 | 194022.38 |
| 2023 | 139523.06 |
| 2024 | 277496.66 |
| 2025 | 356936.3 |
| 2026 | 181430.03 |
| 2027 | 167721.2 |
| 2028 | 158330.25 |
| 2029 | 169640.44 |
| 2030 | 267951.66 |
| 2031 | 239700.17 |
| 2032 | 263797 |
| 2033 | 256229.1 |
| 2034 | 179830.31 |
| 2035 | 227978.62 |
| 2036 | 204761.97 |
| 2037 | 211086.4 |
| 2038 | 322123.34 |
| 2039 | 238438.53 |
| 2040 | 324998.2 |
| 2041 | 305345.38 |
| 2042 | 209690.5 |
| 2043 | 180802.28 |
| 2044 | 171513.06 |
| 2045 | 208370.02 |
| 2046 | 147048.36 |
| 2047 | 142594.36 |
| 2048 | 142097.92 |
| 2049 | 142394.31 |
| 2050 | 175071.61 |
| 2051 | 111503.49 |
| 2052 | 122123.47 |
| 2053 | 152183.52 |
| 2054 | 93517.03 |
| 2055 | 163097.4 |
| 2056 | 147829.11 |
| 2057 | 109119.234 |
| 2058 | 207781.22 |
| 2059 | 132470.1 |
| 2060 | 176975.23 |
| 2061 | 167580.12 |
| 2062 | 134712.11 |
| 2063 | 123643.02 |
| 2064 | 138589.64 |
| 2065 | 115030.41 |
| 2066 | 169285.73 |
| 2067 | 127286.08 |
| 2068 | 151083.06 |
| 2069 | 88952.97 |
| 2070 | 118961.67 |
| 2071 | 101515.51 |
| 2072 | 140298.33 |
| 2073 | 129104.016 |
| 2074 | 173923.36 |
| 2075 | 154631.89 |
| 2076 | 123441.016 |
| 2077 | 162099.64 |
| 2078 | 134382.67 |
| 2079 | 135114.62 |
| 2080 | 120152.42 |
| 2081 | 131781.16 |
| 2082 | 126559.78 |
| 2083 | 152545.48 |
| 2084 | 116902.56 |
| 2085 | 113280.68 |
| 2086 | 112189.19 |
| 2087 | 115796.164 |
| 2088 | 99172.62 |
| 2089 | 89722.25 |
| 2090 | 124407.17 |
| 2091 | 101428.93 |
| 2092 | 126251.3 |
| 2093 | 121644.66 |
| 2094 | 114269.516 |
| 2095 | 141940.73 |
| 2096 | 84063.17 |
| 2097 | 97861.79 |
| 2098 | 144658.33 |
| 2099 | 44223.01 |
| 2100 | 66750.16 |
| 2101 | 110790.17 |
| 2102 | 130570.45 |
| 2103 | 108910.57 |
| 2104 | 144936.27 |
| 2105 | 134286.11 |
| 2106 | 45160.777 |
| 2107 | 198110.92 |
| 2108 | 120122.32 |
| 2109 | 113533.914 |
| 2110 | 117337.47 |
| 2111 | 135028.1 |
| 2112 | 144545.69 |
| 2113 | 121424.38 |
| 2114 | 118727.914 |
| 2115 | 165567.44 |
| 2116 | 120656.79 |
| 2117 | 140580.88 |
| 2118 | 132169.1 |
| 2119 | 117341.516 |
| 2120 | 110728.195 |
| 2121 | 101284.32 |
| 2122 | 123274.88 |
| 2123 | 96835.78 |
| 2124 | 174725.64 |
| 2125 | 122530.61 |
| 2126 | 155744.34 |
| 2127 | 168768.98 |
| 2128 | 127745.305 |
| 2129 | 83005.28 |
| 2130 | 137304.84 |
| 2131 | 138872.56 |
| 2132 | 113818.37 |
| 2133 | 133655.34 |
| 2134 | 120345.29 |
| 2135 | 94670.56 |
| 2136 | 71101.664 |
| 2137 | 110236.64 |
| 2138 | 129179.1 |
| 2139 | 146268.56 |
| 2140 | 147021.5 |
| 2141 | 159648.78 |
| 2142 | 131723.44 |
| 2143 | 151829.06 |
| 2144 | 127240.695 |
| 2145 | 143676.58 |
| 2146 | 183091.67 |
| 2147 | 138432.25 |
| 2148 | 138550.2 |
| 2149 | 143770.45 |
| 2150 | 247216.69 |
| 2151 | 130730.055 |
| 2152 | 171132.39 |
| 2153 | 178200.52 |
| 2154 | 111902.734 |
| 2155 | 142943.14 |
| 2156 | 255033.83 |
| 2157 | 231639.78 |
| 2158 | 243033.5 |
| 2159 | 222531.44 |
| 2160 | 184625.02 |
| 2161 | 240548.9 |
| 2162 | 393289.72 |
| 2163 | 351552.84 |
| 2164 | 251319.16 |
| 2165 | 209541.95 |
| 2166 | 161176.22 |
| 2167 | 218429.67 |
| 2168 | 187555.67 |
| 2169 | 194737.55 |
| 2170 | 213551.28 |
| 2171 | 157005.78 |
| 2172 | 131617.58 |
| 2173 | 188666.36 |
| 2174 | 217066.23 |
| 2175 | 291368.12 |
| 2176 | 314643.56 |
| 2177 | 236666.52 |
| 2178 | 210783.81 |
| 2179 | 137697.14 |
| 2180 | 205902.64 |
| 2181 | 189809.06 |
| 2182 | 221848.8 |
| 2183 | 191664.77 |
| 2184 | 118496.13 |
| 2185 | 121904.22 |
| 2186 | 145080.92 |
| 2187 | 150266.2 |
| 2188 | 161232.69 |
| 2189 | 296636.38 |
| 2190 | 82809.55 |
| 2191 | 71310.76 |
| 2192 | 88425.18 |
| 2193 | 117009.06 |
| 2194 | 103539.48 |
| 2195 | 105856.32 |
| 2196 | 106999.266 |
| 2197 | 125065.95 |
| 2198 | 168102.48 |
| 2199 | 182802.6 |
| 2200 | 140759.62 |
| 2201 | 147901.83 |
| 2202 | 219184.39 |
| 2203 | 138716.88 |
| 2204 | 176221.27 |
| 2205 | 120361.59 |
| 2206 | 146867.94 |
| 2207 | 218074.2 |
| 2208 | 261673.97 |
| 2209 | 258171.39 |
| 2210 | 128679.51 |
| 2211 | 124766.16 |
| 2212 | 129398.68 |
| 2213 | 109898.5 |
| 2214 | 136358.36 |
| 2215 | 108062.695 |
| 2216 | 151577.4 |
| 2217 | 41640.66 |
| 2218 | 84983.37 |
| 2219 | 82679.98 |
| 2220 | 57336.902 |
| 2221 | 332248.75 |
| 2222 | 297581.44 |
| 2223 | 304015.25 |
| 2224 | 220093.08 |
| 2225 | 129612.83 |
| 2226 | 180572.19 |
| 2227 | 200704.56 |
| 2228 | 290906.94 |
| 2229 | 244939 |
| 2230 | 157956 |
| 2231 | 214641.17 |
| 2232 | 178120.25 |
| 2233 | 178078.55 |
| 2234 | 253836.23 |
| 2235 | 224317.12 |
| 2236 | 245801.81 |
| 2237 | 312202.38 |
| 2238 | 202499.16 |
| 2239 | 101278.336 |
| 2240 | 156092.5 |
| 2241 | 137567.67 |
| 2242 | 126049.664 |
| 2243 | 131462.95 |
| 2244 | 105496.57 |
| 2245 | 113423.914 |
| 2246 | 143241.34 |
| 2247 | 127939.55 |
| 2248 | 129330.84 |
| 2249 | 124667.84 |
| 2250 | 133573.77 |
| 2251 | 121154.9 |
| 2252 | 181185.06 |
| 2253 | 163571.56 |
| 2254 | 180182.53 |
| 2255 | 186588.72 |
| 2256 | 174165.08 |
| 2257 | 210190.05 |
| 2258 | 158404.1 |
| 2259 | 178287.83 |
| 2260 | 145563.22 |
| 2261 | 204864.27 |
| 2262 | 218912.17 |
| 2263 | 384536.4 |
| 2264 | 445243.25 |
| 2265 | 167868.03 |
| 2266 | 302303.53 |
| 2267 | 353645.2 |
| 2268 | 407859.66 |
| 2269 | 154690.78 |
| 2270 | 193957.03 |
| 2271 | 209040.34 |
| 2272 | 192115.95 |
| 2273 | 162287.28 |
| 2274 | 184813.92 |
| 2275 | 149662.11 |
| 2276 | 192300.77 |
| 2277 | 179732.94 |
| 2278 | 151006.6 |
| 2279 | 134717.97 |
| 2280 | 110179.75 |
| 2281 | 158346.1 |
| 2282 | 174898.27 |
| 2283 | 114449.99 |
| 2284 | 119659.17 |
| 2285 | 148362.8 |
| 2286 | 125459.87 |
| 2287 | 374330.3 |
| 2288 | 286092 |
| 2289 | 354078.97 |
| 2290 | 419052 |
| 2291 | 349635.16 |
| 2292 | 425485.12 |
| 2293 | 442612.7 |
| 2294 | 397385.12 |
| 2295 | 459371.6 |
| 2296 | 257165.53 |
| 2297 | 369536.28 |
| 2298 | 365585.38 |
| 2299 | 358670.66 |
| 2300 | 323914.6 |
| 2301 | 339191.22 |
| 2302 | 257773.14 |
| 2303 | 243079.5 |
| 2304 | 254137.92 |
| 2305 | 190643.31 |
| 2306 | 185085.48 |
| 2307 | 197270.95 |
| 2308 | 220136.48 |
| 2309 | 290753.28 |
| 2310 | 216837.02 |
| 2311 | 204211.98 |
| 2312 | 179657.16 |
| 2313 | 168135.94 |
| 2314 | 169910.23 |
| 2315 | 180834.47 |
| 2316 | 203061.39 |
| 2317 | 191817.55 |
| 2318 | 177367.33 |
| 2319 | 182393.89 |
| 2320 | 181573.75 |
| 2321 | 252619.55 |
| 2322 | 192489.97 |
| 2323 | 198495.17 |
| 2324 | 187776.56 |
| 2325 | 211307.66 |
| 2326 | 182654.11 |
| 2327 | 196466.34 |
| 2328 | 220435.55 |
| 2329 | 193979.7 |
| 2330 | 183299.69 |
| 2331 | 342326.38 |
| 2332 | 391052.6 |
| 2333 | 324490.5 |
| 2334 | 265112.8 |
| 2335 | 292338.7 |
| 2336 | 311718.16 |
| 2337 | 188344.56 |
| 2338 | 251137.69 |
| 2339 | 224372.33 |
| 2340 | 391687.53 |
| 2341 | 214534.86 |
| 2342 | 234436.83 |
| 2343 | 228446.84 |
| 2344 | 220505.11 |
| 2345 | 230552.53 |
| 2346 | 215707.28 |
| 2347 | 197427.78 |
| 2348 | 253224.02 |
| 2349 | 195799.9 |
| 2350 | 327060.75 |
| 2351 | 259761.55 |
| 2352 | 252175.88 |
| 2353 | 254619.89 |
| 2354 | 149722.03 |
| 2355 | 149936.28 |
| 2356 | 148843.1 |
| 2357 | 188306.86 |
| 2358 | 198336.6 |
| 2359 | 142202.69 |
| 2360 | 122068.38 |
| 2361 | 150708.72 |
| 2362 | 247082.4 |
| 2363 | 150204.95 |
| 2364 | 163834.03 |
| 2365 | 219954.25 |
| 2366 | 192207.81 |
| 2367 | 214773.42 |
| 2368 | 218065.34 |
| 2369 | 211610.56 |
| 2370 | 172103.34 |
| 2371 | 166105.45 |
| 2372 | 182341.78 |
| 2373 | 297192.2 |
| 2374 | 324295.53 |
| 2375 | 253133.95 |
| 2376 | 289657.2 |
| 2377 | 333894.38 |
| 2378 | 152381.05 |
| 2379 | 204237.39 |
| 2380 | 147176.34 |
| 2381 | 172467.61 |
| 2382 | 220246.44 |
| 2383 | 197136.61 |
| 2384 | 240572.64 |
| 2385 | 164499.44 |
| 2386 | 136833.17 |
| 2387 | 134753.81 |
| 2388 | 110968.04 |
| 2389 | 117281.49 |
| 2390 | 151502.4 |
| 2391 | 140846.95 |
| 2392 | 116947.23 |
| 2393 | 169917.58 |
| 2394 | 153555.61 |
| 2395 | 205573.97 |
| 2396 | 150360.98 |
| 2397 | 206533.27 |
| 2398 | 126279.98 |
| 2399 | 72818.24 |
| 2400 | 71322.14 |
| 2401 | 129686.34 |
| 2402 | 137327.97 |
| 2403 | 146756.39 |
| 2404 | 154330.98 |
| 2405 | 151309.4 |
| 2406 | 151854.06 |
| 2407 | 131574.25 |
| 2408 | 144814.9 |
| 2409 | 115721.08 |
| 2410 | 171317.77 |
| 2411 | 121974.8 |
| 2412 | 160726.56 |
| 2413 | 132760.6 |
| 2414 | 162108.78 |
| 2415 | 130328.52 |
| 2416 | 135343.7 |
| 2417 | 143860.56 |
| 2418 | 141242.03 |
| 2419 | 127419.64 |
| 2420 | 129849.37 |
| 2421 | 163377.73 |
| 2422 | 111643.7 |
| 2423 | 122383.91 |
| 2424 | 144792.58 |
| 2425 | 225499.86 |
| 2426 | 138591.94 |
| 2427 | 136678.97 |
| 2428 | 183659.38 |
| 2429 | 113430.414 |
| 2430 | 137063.95 |
| 2431 | 113561.51 |
| 2432 | 153972.45 |
| 2433 | 151572.14 |
| 2434 | 145035.22 |
| 2435 | 161557.72 |
| 2436 | 116302.664 |
| 2437 | 102715.89 |
| 2438 | 126103.8 |
| 2439 | 96591.82 |
| 2440 | 125398.04 |
| 2441 | 99778.336 |
| 2442 | 97932.27 |
| 2443 | 135904.86 |
| 2444 | 121821.74 |
| 2445 | 85885.48 |
| 2446 | 145485.69 |
| 2447 | 211815.22 |
| 2448 | 129222.945 |
| 2449 | 114076.12 |
| 2450 | 156374.14 |
| 2451 | 114435.43 |
| 2452 | 222595.45 |
| 2453 | 96624.28 |
| 2454 | 122842.63 |
| 2455 | 121348.945 |
| 2456 | 134501.95 |
| 2457 | 141751.47 |
| 2458 | 146727.33 |
| 2459 | 116910.02 |
| 2460 | 143859.1 |
| 2461 | 132618.11 |
| 2462 | 129880.16 |
| 2463 | 134224.11 |
| 2464 | 186559.56 |
| 2465 | 138502.6 |
| 2466 | 118483.8 |
| 2467 | 126863.45 |
| 2468 | 93665.586 |
| 2469 | 88803.71 |
| 2470 | 198236.06 |
| 2471 | 224244.11 |
| 2472 | 161246.06 |
| 2473 | 114601.3 |
| 2474 | 66104.6 |
| 2475 | 204116.98 |
| 2476 | 125858.11 |
| 2477 | 127140.09 |
| 2478 | 149940.97 |
| 2479 | 106027.08 |
| 2480 | 160687.84 |
| 2481 | 132111.19 |
| 2482 | 123184.72 |
| 2483 | 112890.47 |
| 2484 | 122489.97 |
| 2485 | 128951.23 |
| 2486 | 148654.94 |
| 2487 | 180646.75 |
| 2488 | 174067.31 |
| 2489 | 160982.58 |
| 2490 | 143080.02 |
| 2491 | 94024.46 |
| 2492 | 196978 |
| 2493 | 154928.77 |
| 2494 | 150010.67 |
| 2495 | 89149.05 |
| 2496 | 238773.03 |
| 2497 | 157265.81 |
| 2498 | 118202.01 |
| 2499 | 88147.72 |
| 2500 | 123940.305 |
| 2501 | 145016.12 |
| 2502 | 143711.98 |
| 2503 | 94850.53 |
| 2504 | 195490.58 |
| 2505 | 223512.8 |
| 2506 | 261058.81 |
| 2507 | 286793.8 |
| 2508 | 258462.72 |
| 2509 | 221906.27 |
| 2510 | 213150.73 |
| 2511 | 176646.89 |
| 2512 | 209559.72 |
| 2513 | 221530.02 |
| 2514 | 255595.39 |
| 2515 | 153251.98 |
| 2516 | 178609 |
| 2517 | 149428.92 |
| 2518 | 159331.88 |
| 2519 | 247287.48 |
| 2520 | 217945.05 |
| 2521 | 188419.1 |
| 2522 | 220408.23 |
| 2523 | 117609.234 |
| 2524 | 140594.92 |
| 2525 | 147730.52 |
| 2526 | 146340.33 |
| 2527 | 130671.81 |
| 2528 | 132177.69 |
| 2529 | 147370.94 |
| 2530 | 126139.04 |
| 2531 | 257784.05 |
| 2532 | 218978.11 |
| 2533 | 195885.39 |
| 2534 | 237339.34 |
| 2535 | 272649.9 |
| 2536 | 225914.67 |
| 2537 | 251659.62 |
| 2538 | 186148.67 |
| 2539 | 189729.27 |
| 2540 | 179237.67 |
| 2541 | 180269.45 |
| 2542 | 165571.72 |
| 2543 | 117570.57 |
| 2544 | 114610.54 |
| 2545 | 131735.94 |
| 2546 | 119243.71 |
| 2547 | 142803.61 |
| 2548 | 163151.98 |
| 2549 | 161609.86 |
| 2550 | 601652.06 |
| 2551 | 135516.58 |
| 2552 | 136533.53 |
| 2553 | 72865.49 |
| 2554 | 94654.01 |
| 2555 | 112978.17 |
| 2556 | 102819.47 |
| 2557 | 102172.75 |
| 2558 | 142799.8 |
| 2559 | 147077.06 |
| 2560 | 162926.69 |
| 2561 | 165914.19 |
| 2562 | 150986.39 |
| 2563 | 160101.84 |
| 2564 | 215008.94 |
| 2565 | 155047.75 |
| 2566 | 153758.44 |
| 2567 | 143647.11 |
| 2568 | 226278.08 |
| 2569 | 233726.73 |
| 2570 | 122256.99 |
| 2571 | 186426.62 |
| 2572 | 158949.83 |
| 2573 | 212469.56 |
| 2574 | 291310.88 |
| 2575 | 135158.92 |
| 2576 | 119016.02 |
| 2577 | 154596.25 |
| 2578 | 81782.1 |
| 2579 | 51383.03 |
| 2580 | 110637.27 |
| 2581 | 124629.945 |
| 2582 | 130377.04 |
| 2583 | 289046.7 |
| 2584 | 170571.88 |
| 2585 | 188656.94 |
| 2586 | 214893.97 |
| 2587 | 201812.16 |
| 2588 | 141840.11 |
| 2589 | 150328.19 |
| 2590 | 207862.7 |
| 2591 | 233368.78 |
| 2592 | 208596.53 |
| 2593 | 264846.12 |
| 2594 | 179507.44 |
| 2595 | 215715.67 |
| 2596 | 302486.12 |
| 2597 | 191534.98 |
| 2598 | 291180.06 |
| 2599 | 349501.8 |
| 2600 | 180779.86 |
| 2601 | 139190.66 |
| 2602 | 83705.055 |
| 2603 | 98934.6 |
| 2604 | 93266.305 |
| 2605 | 77140.37 |
| 2606 | 138894.8 |
| 2607 | 233493.45 |
| 2608 | 193336.62 |
| 2609 | 164557.31 |
| 2610 | 115403.32 |
| 2611 | 126382.81 |
| 2612 | 159627.47 |
| 2613 | 135525.84 |
| 2614 | 127000.37 |
| 2615 | 159132.1 |
| 2616 | 150348 |
| 2617 | 184961.7 |
| 2618 | 213836.86 |
| 2619 | 196961.1 |
| 2620 | 189848.1 |
| 2621 | 176502.16 |
| 2622 | 179428.42 |
| 2623 | 229164.31 |
| 2624 | 316093.84 |
| 2625 | 265468.3 |
| 2626 | 176227.98 |
| 2627 | 171410.34 |
| 2628 | 470755.38 |
| 2629 | 495089.75 |
| 2630 | 393298.66 |
| 2631 | 451260.4 |
| 2632 | 420568.22 |
| 2633 | 305837.16 |
| 2634 | 416986.53 |
| 2635 | 155537.7 |
| 2636 | 175702.02 |
| 2637 | 185370.64 |
| 2638 | 257548.7 |
| 2639 | 191661.78 |
| 2640 | 156254.28 |
| 2641 | 108398.67 |
| 2642 | 175592.44 |
| 2643 | 111263.67 |
| 2644 | 114680.36 |
| 2645 | 116768.43 |
| 2646 | 102252.92 |
| 2647 | 108196.27 |
| 2648 | 143867.12 |
| 2649 | 155532.64 |
| 2650 | 137735.6 |
| 2651 | 145672.55 |
| 2652 | 389321.84 |
| 2653 | 257187.16 |
| 2654 | 267012.22 |
| 2655 | 411279.2 |
| 2656 | 341335.7 |
| 2657 | 346895.2 |
| 2658 | 316990.94 |
| 2659 | 332261.3 |
| 2660 | 369979.1 |
| 2661 | 354312.94 |
| 2662 | 375499.7 |
| 2663 | 289439.3 |
| 2664 | 283664.94 |
| 2665 | 348070.72 |
| 2666 | 287234.9 |
| 2667 | 175112.31 |
| 2668 | 181750.22 |
| 2669 | 181159.69 |
| 2670 | 282026.97 |
| 2671 | 189440.86 |
| 2672 | 198141.03 |
| 2673 | 198487.3 |
| 2674 | 196260.47 |
| 2675 | 185919.77 |
| 2676 | 192388.66 |
| 2677 | 201286.78 |
| 2678 | 258150.94 |
| 2679 | 290246.25 |
| 2680 | 294213.9 |
| 2681 | 405299.75 |
| 2682 | 321328.78 |
| 2683 | 508680.8 |
| 2684 | 330902.4 |
| 2685 | 331281.06 |
| 2686 | 242294 |
| 2687 | 310977 |
| 2688 | 207423.61 |
| 2689 | 212617.83 |
| 2690 | 380654.47 |
| 2691 | 192578.56 |
| 2692 | 151010.28 |
| 2693 | 200119.56 |
| 2694 | 142326.97 |
| 2695 | 194065.02 |
| 2696 | 184748.23 |
| 2697 | 184349.38 |
| 2698 | 194030.22 |
| 2699 | 174918.75 |
| 2700 | 157508.53 |
| 2701 | 154297.9 |
| 2702 | 105564.125 |
| 2703 | 126416.11 |
| 2704 | 141684.62 |
| 2705 | 120513.445 |
| 2706 | 106173.85 |
| 2707 | 122666.94 |
| 2708 | 144020.61 |
| 2709 | 116650.516 |
| 2710 | 134149.4 |
| 2711 | 300130.44 |
| 2712 | 403024.47 |
| 2713 | 167749.86 |
| 2714 | 155467.1 |
| 2715 | 172156.36 |
| 2716 | 151135.48 |
| 2717 | 188180.97 |
| 2718 | 210707.75 |
| 2719 | 154782.28 |
| 2720 | 170810.66 |
| 2721 | 136786.94 |
| 2722 | 155734.19 |
| 2723 | 137525.22 |
| 2724 | 133630.1 |
| 2725 | 137949.47 |
| 2726 | 147697.5 |
| 2727 | 169739.1 |
| 2728 | 181759.98 |
| 2729 | 151593.92 |
| 2730 | 149981.62 |
| 2731 | 142147.88 |
| 2732 | 138951.66 |
| 2733 | 157194.3 |
| 2734 | 137362.67 |
| 2735 | 143752.4 |
| 2736 | 142289.44 |
| 2737 | 128671.41 |
| 2738 | 139429.33 |
| 2739 | 161054 |
| 2740 | 141852.16 |
| 2741 | 149200.92 |
| 2742 | 153761.55 |
| 2743 | 153570.75 |
| 2744 | 164076.56 |
| 2745 | 144147.95 |
| 2746 | 148568.83 |
| 2747 | 154024.52 |
| 2748 | 126629.03 |
| 2749 | 131272 |
| 2750 | 132642.34 |
| 2751 | 139764.47 |
| 2752 | 209060.42 |
| 2753 | 144967.8 |
| 2754 | 230085.5 |
| 2755 | 144699.88 |
| 2756 | 98313.75 |
| 2757 | 60826.055 |
| 2758 | 96869.82 |
| 2759 | 172173.58 |
| 2760 | 122414.04 |
| 2761 | 142972.36 |
| 2762 | 145225.86 |
| 2763 | 183214.47 |
| 2764 | 145924.17 |
| 2765 | 289901.25 |
| 2766 | 127482.88 |
| 2767 | 90084.16 |
| 2768 | 131764.67 |
| 2769 | 143638.39 |
| 2770 | 143414.11 |
| 2771 | 108466.26 |
| 2772 | 111305.04 |
| 2773 | 186153.73 |
| 2774 | 142050.33 |
| 2775 | 116780.68 |
| 2776 | 145638.97 |
| 2777 | 144850.75 |
| 2778 | 114150.586 |
| 2779 | 122828.06 |
| 2780 | 94048.34 |
| 2781 | 98965.93 |
| 2782 | 97332.95 |
| 2783 | 99300.56 |
| 2784 | 124576.95 |
| 2785 | 138322.17 |
| 2786 | 67104.89 |
| 2787 | 127814.27 |
| 2788 | 76001.29 |
| 2789 | 170853.77 |
| 2790 | 100689.85 |
| 2791 | 106826.56 |
| 2792 | 59853.004 |
| 2793 | 147052.72 |
| 2794 | 96232.664 |
| 2795 | 122626.836 |
| 2796 | 107979.84 |
| 2797 | 191597.5 |
| 2798 | 104082.88 |
| 2799 | 109486.15 |
| 2800 | 70032.94 |
| 2801 | 112445.57 |
| 2802 | 126304.87 |
| 2803 | 159996.97 |
| 2804 | 134879.28 |
| 2805 | 112202.266 |
| 2806 | 87541.875 |
| 2807 | 166501.42 |
| 2808 | 149769.77 |
| 2809 | 134519.72 |
| 2810 | 134378.12 |
| 2811 | 167283.14 |
| 2812 | 169449.86 |
| 2813 | 157022.11 |
| 2814 | 157688.19 |
| 2815 | 101212.88 |
| 2816 | 229828.2 |
| 2817 | 161482.17 |
| 2818 | 131381.7 |
| 2819 | 182258.72 |
| 2820 | 142963.02 |
| 2821 | 109002.945 |
| 2822 | 193043.33 |
| 2823 | 320973.53 |
| 2824 | 178535.62 |
| 2825 | 145867.34 |
| 2826 | 130547.46 |
| 2827 | 136262.52 |
| 2828 | 218970 |
| 2829 | 218833.94 |
| 2830 | 221957.03 |
| 2831 | 185279.03 |
| 2832 | 234602.19 |
| 2833 | 321863.28 |
| 2834 | 227306.14 |
| 2835 | 225863.34 |
| 2836 | 192867.17 |
| 2837 | 160578.31 |
| 2838 | 150346.61 |
| 2839 | 168093.92 |
| 2840 | 203082.12 |
| 2841 | 203636.52 |
| 2842 | 231202.58 |
| 2843 | 156672.2 |
| 2844 | 171455.25 |
| 2845 | 134274.86 |
| 2846 | 205142.78 |
| 2847 | 212508 |
| 2848 | 204855.81 |
| 2849 | 196940.34 |
| 2850 | 284461.16 |
| 2851 | 204536.89 |
| 2852 | 232994.8 |
| 2853 | 231694.73 |
| 2854 | 142950.17 |
| 2855 | 203375.53 |
| 2856 | 198280.73 |
| 2857 | 189020.25 |
| 2858 | 206838.31 |
| 2859 | 101252.484 |
| 2860 | 132006.53 |
| 2861 | 129369.055 |
| 2862 | 184794.3 |
| 2863 | 140459.23 |
| 2864 | 247967.11 |
| 2865 | 139382.81 |
| 2866 | 139204.3 |
| 2867 | 102740.695 |
| 2868 | 94933.8 |
| 2869 | 91648.83 |
| 2870 | 119731.695 |
| 2871 | 74300.68 |
| 2872 | 45479.25 |
| 2873 | 97251.53 |
| 2874 | 145662.03 |
| 2875 | 113528.95 |
| 2876 | 163768.38 |
| 2877 | 158042.22 |
| 2878 | 156925.62 |
| 2879 | 143938.95 |
| 2880 | 110444.18 |
| 2881 | 152585.5 |
| 2882 | 184830.83 |
| 2883 | 194566.44 |
| 2884 | 210717.2 |
| 2885 | 189722.42 |
| 2886 | 239812.06 |
| 2887 | 106130.22 |
| 2888 | 149209.53 |
| 2889 | 53087.24 |
| 2890 | 88317.62 |
| 2891 | 141692.03 |
| 2892 | 39564.46 |
| 2893 | 81548.22 |
| 2894 | 54232.34 |
| 2895 | 336280.34 |
| 2896 | 293739.4 |
| 2897 | 224354.12 |
| 2898 | 146859.1 |
| 2899 | 211767.02 |
| 2900 | 163121.3 |
| 2901 | 219632.66 |
| 2902 | 182716.48 |
| 2903 | 323931.12 |
| 2904 | 348629 |
| 2905 | 77044.79 |
| 2906 | 197792.22 |
| 2907 | 114987.61 |
| 2908 | 134429.4 |
| 2909 | 146392.9 |
| 2910 | 80375.74 |
| 2911 | 84686.83 |
| 2912 | 153530.78 |
| 2913 | 76145.88 |
| 2914 | 75837.03 |
| 2915 | 86668.09 |
| 2916 | 81517.31 |
| 2917 | 167503.38 |
| 2918 | 115305.73 |
| 2919 | 232117.42 |
原文地址：https://blog.csdn.net/zxqq_/article/details/144447004
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