0
100% Satisfaction Guarantee
Amazing Value
Fast Shipping
Expert Customer Service
Python医学实用统计分析
$51.64
本书主要介绍与数据分析有关的语法基础,针对性强,帮助读者快速入门,譬如在第2部分重点介绍了Python入门语法、特征以及数据分析所需要的一些基本语法。Python可以通过多个库、多种方法实现相同目的,如实现线性回归可以用sklearn、statsmodels等库,实现生存分析可以使用lifelines、pysurvival、statsmodels等库,并且存在很多代码不统一的情况,这会给初学者带来困惑。针对这个问题,本书主要使用...
本书主要介绍与数据分析有关的语法基础,针对性强,帮助读者快速入门,譬如在第2部分重点介绍了Python入门语法、特征以及数据分析所需要的一些基本语法。Python可以通过多个库、多种方法实现相同目的,如实现线性回归可以用sklearn、statsmodels等库,实现生存分析可以使用lifelines、pysurvival、statsmodels等库,并且存在很多代码不统一的情况,这会给初学者带来困惑。针对这个问题,本书主要使用Scipy库来实现假设检验,使用statsmodels库来拟合统计模型,并且尽量使用简洁的代码来完成数据分析,譬如在第7部分中介绍了利用Pandas库在同步完成数据清洗和统计图绘制,减少代码书写量,提高数据分析效率。本书的编写突出实用性,注重数据前期处理与医学统计分析相结合;按照资料类型介绍统计学方法,有利于读者在实际数据分析中快速查找对应的统计学方法;在介绍每种统等
潘兴强:流行病与卫生统计学专业,擅长医学统计与大数据分析。近年来主持课题4项,其中省部级课题1项,省厅级课题1项,市厅级课题1项;以作者发表论文18篇,其中SCI收录3篇,中华级5篇,影响因子7.023,参编专业书籍《流行病学数据分析与易侕统计软件实现》。
1 Python 简介与安装/ 11.1 Python 的优点/ 11.2 Python 的安装与配置/ 21.2.1 Windows 系统下的安装与配置/ 31.2.2 Mac 系统下的安装与配置/ 61.2.3 Linux 系统下的安装与配置/ 61.3 Anaconda 的使用方法/ 61.3.1 打开命令行终端/ 61.3.2 更新软件下载渠道/ 61.3.3 创建conda 虚拟环境/ 71.3.4 安装软件库/ 71.3.5 conda 常用命令合集/ 71.4 Jupyter Notebook/ 81.4.1 打开Jupyter Notebook/ 91.4.2 Jupyter Notebook 界面/ 92 Python 语言基础与重要的库/ 162.1 Python 快速入门/ 162.1.1 个Python 程序/ 162.1.2 Python 的缩进/ 172.1.3 查询帮助文件/ 172.1.4 Tab 键自动补全代码/ 182.2 Python 语法基础/ 182.2.1 变量和数据类型/ 182.2.2 运算符/ 192.2.3 列表、元组和字典/ 212.2.4 函数/ 212.3 重要的Python 库/ 223 数据集创建/ 243.1 NumPy 多维数组对象/ 253.1.1 NumPy 数组属性/ 253.1.2 NumPy 数组创建/ 273.1.3 NumPy 切片和索引/ 303.2 Pandas 数据结构/ 323.2.1 Series(一维数据)/ 323.2.2 DataFrame(二维数据)/ 333.2.3 NumPy 与Pandas 转换/ 363.3 数据取值与选择/ 363.3.1 Series(一维数据)/ 363.3.2 DataFrame(二维数据)/ 383.4 数据读取与存储/ 413.4.1 Pandas 读取Excel 数据/ 413.4.2 Pandas 读取CSV 文件/ 423.4.3 Pandas 读取Txt 数据/ 433.4.4 Pandas 读取SAS、Stata 和SPSS 数据/ 453.4.5 存储数据/ 464 基本数据管理/ 474.1 数据基本信息与结构查看/ 474.2 创建新变量/ 494.3 变量重命名/ 504.4 数据类型转换 / 524.4.1 基本数据类型转换/ 524.4.2 时间日期数据类型转换/ 534.5 数据排序/ 564.5.1 按索引标签排序/ 564.5.2 按列值排序/ 574.6 缺失值处理/ 584.6.1 缺失值判断/ 584.6.2 缺失值删除/ 604.7 缺失数据填补/ 624.8 重复数据处理/ 634.9 数据集的合并/ 654.9.1 merge( ) 方法/ 654.9.2 concat( ) 方法/ 674.9.3 join( ) 方法/ 704.10 数据集取子集/ 724.10.1 直接选择/ 724.10.2 loc( ) 函数选取子集/ 734.10.3 iloc( ) 函数选取子集/ 744.11 数据分组/ 754.11.1 groupby( ) 函数/ 754.11.2 cut( ) 和qcut( ) 函数/ 774.12 melt( ) 函数/ 804.13 数据集更新/ 814.13.1 replace( ) 函数/ 814.13.2 update( ) 函数/ 814.14 数据集比较/ 835 高级数据管理/ 865.1 控制流/ 865.1.1 条件(分支)语句/ 865.1.2 循环结构/ 885.2 函数/ 915.2.1 pandas 函数/ 915.2.2 lambda 函数/ 955.3 向量化字符串操作/ 965.4 正则表达式/ 1006 网络数据采集/ 1056.1 初识爬虫/ 1056.2 http 协议与url/ 1066.2.1 http 请求/ 1076.2.2 http 响应/ 1076.3 网页结构/ 1086.3.1 HTML 标签/ 1086.3.2 HTML 属性/ 1096.4 Requests 库/ 1096.4.1 获取网页/ 1096.4.2 POST 请求/ 1116.5 BeautifulSoup 库/ 1116.5.1 BeautifulSoup 对象/ 1116.5.2 BeautifulSoup 标签/ 1136.5.3 遍历节点/ 1146.5.4 方法选择器/ 1157 资料类型及展示/ 1177.1 资料类型/ 1177.2 统计描述/ 1187.2.1 定量资料/ 1187.2.2 定性资料/ 1237.3 数据透视表/ 1247.4 表格重塑/ 1257.5 绘制图形/ 1297.5.1 绘制图形的基本步骤/ 1297.5.2 常见统计图/ 1307.5.3 子图绘制/ 1397.5.4 金字塔图/ 1407.5.5 其他图形绘制/ 1428 定量资料统计方法/ 1438.1 单样本资料与已知总体参数比较/ 1438.1.1 单样本资料的t 检验/ 1438.1.2 Wilcoxon 符号秩和检验/ 1448.2 两组资料之间的比较/ 1458.2.1 配对t 检验/ 1458.2.2 配对设计资料的非参数检验/ 1478.2.3 两组独立样本的t 检验/ 1488.2.4 两组资料的非参数检验/ 1498.3 两组以上资料比较/ 1508.3.1 方差分析/ 1508.3.2 Kruskal-Wallis H 检验/ 1538.4 相关分析/ 1548.4.1 直线相关分析/ 1548.4.2 秩相关/ 1578.5 线性回归分析/ 1588.5.1 基本原理/ 1588.5.2 应用条件/ 1598.5.3 线性回归分析的Python 实现/ 1599 分类资料数据分析/ 1629.1 卡方检验/ 1629.1.1 四格表资料的卡方检验/ 1629.1.2 R×C 列联表资料的卡方检验/ 1639.1.3 卡方检验的选用/ 1639.1.4 卡方检验的Python 实现/ 1649.2 Fisher 确切概率法/ 1669.2.1 Fisher 确切概率法使用条件/ 1669.2.2 Fisher 确切概率法的Python 实现/ 1669.3 配对卡方检验/ 1679.3.1 配对卡方检验使用条件/ 1689.3.2 配对卡方检验的Python 实现/ 1689.4 多个相关样本的非参数检验(Cochran Q 检验)/ 1699.4.1 Cochran Q 检验的Python 实现/ 1699.5 趋势卡方检验/ 1709.5.1 趋势卡方检验的Python 实现/ 17010 多重线性回归/ 17210.1 多重线性回归分析/ 17210.1.1 多重线性回归模型简介/ 17210.1.2 多重线性回归使用条件/ 17310.1.3 资料格式/ 17410.1.4 多重线性回归分析的Python 实现/ 17410.2 自变量筛选/ 17610.2.1 逐步回归分析的Python 实现/ 17710.3 多重共线性和回归诊断/ 18110.3.1 共线性诊断/ 18110.3.2 模型诊断/ 18211 logistic 回归/ 18411.1 二分类logistic 回归/ 18411.1.1 二分类logistic 回归的使用条件/ 18511.1.2 资料格式/ 18511.1.3 logistic 回归的Python 实现/ 18511.1.4 广义线性模型/ 19211.2 有序logistic 回归/ 19511.2.1 资料格式/ 19611.2.2 有序多分类logistic 回归的Python 实现/ 19611.3 无序多分类logistic 回归/ 19911.3.1 资料格式/ 20011.3.2 多分类无序logistic 回归的Python 实现/ 20011.4 条件logistic 回归/ 20311.4.1 资料格式/ 20311.4.2 条件logistic 回归的Python 实现/ 20412 Poisson 回归/ 20712.1 Poisson 回归的应用条件/ 20712.2 资料格式/ 20812.3 利用广义线性模型实现Poisson 回归/ 21213 生存分析/ 21413.1 基本概念/ 21413.1.1 生存时间/ 21413.1.2 生存时间资料的类型/ 21513.1.3 生存概率、生存率与风险函数/ 21513.2 生存分析研究的主要内容/ 21513.3 生存率的估计与组间比较/ 21613.4 中位生存时间与生存曲线/ 21713.5 Cox 比例风险模型/ 21913.5.1 Cox 模型简介/ 22013.5.2 Cox 模型分析的资料格式/ 22113.5.3 Cox 模型分析的Python 实现/ 22113.5.4 Cox 模型分析注意事项/ 22414 时间序列分析/ 22514.1 时间序列的预处理/ 22514.1.1 平稳性检验/ 22614.1.2 纯随机性检验/ 22614.2 平稳时间序列建模/ 22614.3 非平稳时间序列预处理/ 22714.4 ARIMA 模型/ 22814.4.1 资料格式/ 22814.4.2 ARIMA 模型的Python 实现/ 22914.5 季节性ARIMA 模型/ 237
Shipping Overview:
• Shipping: Standard Domestic Shipping within the United States charges USD 4.99. Standard International Shipping from United Kingdom, Germany and Japan to the United States charges 14.99.
• Order Processing: Please allow 1-2 business days for order processing and preparation before shipment.
• Domestic Shipping: Orders within the U.S. are shipped via USPS or FedEx, depending on the origin of the product. The average transit time is 3-7 business days.
• International Shipping: Currently, we only ship within the USA.
• Tracking Information: Every order is trackable. You will receive a tracking number once your order has been shipped. Products may be shipped from various global fulfillment centers.
Shipping Delays:
Please note that shipping times may vary due to factors beyond our control, such as weather conditions, natural disasters, or peak holiday periods. While we strive to ensure timely delivery, the exact arrival time cannot be guaranteed and is managed by the shipping carrier.
Shipping Options:
Standard Delivery: Most orders are shipped within 3-7 business days. Larger items may utilize LTL shipping for safe handling.
Handling Time: We handle shipments on business days (Monday - Friday), with a preparation time of 1-2 days.
Additional Charges: Some items require additional shipping charges due to their size, weight, or special handling. These charges are specified on the product pages and are not eligible for shipping discounts.
Exclusions: Gift cards, packaging, taxes, and prior purchases do not count toward the minimum purchase requirement for free shipping. This offer is valid only for shipments to U.S. addresses, including Puerto Rico.
Delivery Details:
Estimates: Standard shipping within the US typically takes 3-7 business days. These are estimates and not guarantees.
Shipping Restrictions: We ship to all 50 states, Washington, DC, U.S. territories, and APO/FPO/DPO addresses. Shipping options vary based on the delivery address.
Remote Areas: Shipments to remote areas may incur additional charges or require pickup from a nearby shipping partner’s location.
Shipping Confirmation:
You will receive a shipping confirmation email with a tracking number as soon as your order is dispatched. If you do not receive this email immediately, please be assured that your items will arrive within the estimated delivery window provided at checkout.
Order Modifications:
If you need to cancel or modify your order, please contact our customer support immediately.
Issues with Delivery:
If your order shows as delivered but you have not received it, please contact the shipping carrier directly to resolve the issue. For persistent problems, contact our customer service at cs@everymarket.com.
Customer Support:
Our team is available 24/7 to assist you with any questions or concerns regarding your order. We are committed to ensuring a smooth shopping experience.
Return & Refund Policy Overview
Please review our return and refund policies below to ensure a smooth transaction process.
Return Policy
Duration: You have 30 days from receiving your item to initiate a return.
Condition: Items must be unworn, unwashed, with original tags and packaging intact.
Shipping Costs: Customers are responsible for return shipping costs.
Packaging: Ensure returned items are well-packaged to avoid damage during transit.
Tracking: Use a trackable and insured shipping method as we are not liable for items lost or damaged on return.
Initiating a Return: Contact us at cs@everymarket.com to start your return. We will provide a return shipping label and instructions upon approval. Returns without prior approval will not be accepted.
How to Return
Method: Returns must be sent back by mail to the address provided in the return instructions.
Return Label
Defective Products: Return labels are provided for defective items.
Non-Defective Returns: Customers are responsible for obtaining their return shipping label.
Product Conditions for Return
Eligible Products: Returns are only accepted for items in new condition.
Nonreturnable Items
Certain items are not eligible for return:
Electronic devices after 30 days (e.g., computers, laptops, Kindles)
Gift cards, prepaid game cards
Perishable goods, live insects, some jewelry, some health and personal care items
Customized or personalized products
Items with special shipping restrictions
Refund Policy
Window: Eligible products may be returned within 30 days of delivery for a refund.
Refund Method: Refunds are processed to the original payment method or as store credit for items purchased with gift cards.
Processing Time: Refunds are processed within 3-5 business days after we receive the return; please allow additional time for shipping and bank processing.
Claims
Inspect your order upon arrival and report any defects, damages, or incorrect items immediately to allow us to address the issue. For claims, contact our support team with details of the issue.
Exchange Policy
For the quickest service, return your original item and place a new order for the desired product once your return is accepted.
Return Address
EveryMarket Customer Service 2101 E Terra Ln, O'Fallon, MO 63366
Customer Support
Available 24/7 for any questions or assistance needed:
Phone: +1 636-312-5925
Email: cs@everymarket.com
Oops!
Sorry, it looks like some products are not available in selected quantity.
OK