數(shù)據(jù)科學(xué)方法與實(shí)踐 ——基于 Python 技術(shù)實(shí)現(xiàn)
定 價(jià):75 元
- 作者:馬學(xué)強(qiáng)
- 出版時(shí)間:2022/1/1
- ISBN:9787121428173
- 出 版 社:電子工業(yè)出版社
- 中圖法分類:TP274
- 頁碼:397
- 紙張:
- 版次:01
- 開本:16開
本書系統(tǒng)介紹數(shù)據(jù)科學(xué)的核心概念、基本方法和關(guān)鍵技術(shù),內(nèi)容涵蓋數(shù)據(jù)科學(xué)的導(dǎo)向目標(biāo),涉及科學(xué)計(jì)算、數(shù)據(jù)處理和分析、數(shù)據(jù)可視化等關(guān)鍵知識(shí)環(huán)節(jié)。本書基于 Python 技術(shù)框架實(shí)現(xiàn),內(nèi)容注重理論和實(shí)踐的有機(jī)融合,克服單調(diào)、晦澀的知識(shí)累積之苦,以問題為導(dǎo)向,學(xué)以致用,提供了大量的案例代碼和樣本數(shù)據(jù)集,可以為學(xué)習(xí)者平添幾分學(xué)習(xí)的樂趣。本書既適用于高等院!皵(shù)據(jù)科學(xué)與大數(shù)據(jù)技術(shù)”專業(yè)人才的基礎(chǔ)培養(yǎng),也適用于信息處理相關(guān)專業(yè)人才的能力提升,能夠?yàn)閿?shù)據(jù)科學(xué)從業(yè)者和相關(guān)學(xué)科的科研工作者提供必要的技術(shù)支撐。
馬學(xué)強(qiáng),漢族,1970年10月出生,山東壽光人,中共黨員,2015年6月畢業(yè)于山東師范大學(xué)管理工程與工業(yè)工程專業(yè),獲工學(xué)博士學(xué)位。現(xiàn)為山東師范大學(xué)信息科學(xué)與工程學(xué)院副教授。 主要從事虛擬植物模型、進(jìn)化計(jì)算的理論與應(yīng)用研究。參與國家級(jí)、省級(jí)課題多項(xiàng),主持省級(jí)和校級(jí)教學(xué)改革項(xiàng)目多項(xiàng);在EI檢索及其它國內(nèi)外著名學(xué)術(shù)期刊及國際會(huì)議上發(fā)表論文10多篇;獲得山東省科技進(jìn)步一等獎(jiǎng)1項(xiàng)(第6位)、山東省計(jì)算機(jī)應(yīng)用優(yōu)秀成果一等獎(jiǎng)1項(xiàng)(第5位),山東省高等教育教學(xué)成果一等獎(jiǎng)1項(xiàng)(第3位)。
目 錄
第 1 章 數(shù)據(jù)科學(xué)概述 ··················································································1
1.1 什么是數(shù)據(jù)科學(xué)? ············································································1
1.2 大數(shù)據(jù)技術(shù)·····················································································6
1.3 數(shù)據(jù)未來·····················································································.20
第 2 章 Python 基礎(chǔ)··················································································.23
2.1 編程環(huán)境與規(guī)范············································································.23
2.2 數(shù)據(jù)類型、數(shù)據(jù)載體及運(yùn)算 ····························································.25
2.3 序列結(jié)構(gòu)·····················································································.30
2.4 程序流程控制···············································································.38
2.5 函數(shù)···························································································.40
2.6 字符串························································································.45
2.7 文件操作·····················································································.50
2.8 面向?qū)ο蟪绦蛟O(shè)計(jì)·········································································.51
第 3 章 科學(xué)計(jì)算—— Numpy······································································.57
3.1 計(jì)算基礎(chǔ)·····················································································.58
3.1.1 什么是科學(xué)計(jì)算? ·······························································.58
3.1.2 Numpy 基礎(chǔ)········································································.62
3.2 數(shù)組的創(chuàng)建與訪問·········································································.65
3.2.1 創(chuàng)建數(shù)組 ···········································································.66
3.2.2 數(shù)組的訪問 ········································································.72
3.3 數(shù)組的基本操作············································································.74
3.4 數(shù)組的基本運(yùn)算············································································.85
3.5 矩陣基礎(chǔ)及運(yùn)算············································································112
3.6 Numpy 的簡(jiǎn)單應(yīng)用········································································127
第 4 章 數(shù)據(jù)處理和分析—— Pandas ·····························································135
4.1 數(shù)據(jù)結(jié)構(gòu)·····················································································136
4.1.1 常用數(shù)據(jù)結(jié)構(gòu) ·····································································136
4.1.2 數(shù)據(jù)類型 ···········································································137
4.1.3 數(shù)據(jù)類型的簡(jiǎn)單使用 ····························································138
4.1.4 系列的基本使用 ··································································140.VI·
4.1.5 數(shù)據(jù)幀的基本使用 ·······························································145
4.2 數(shù)據(jù)加載與文件格式······································································154
4.2.1 Pandas 的 I/O 功能································································155
4.2.2 數(shù)據(jù)讀寫與文件格式 ····························································158
4.3 數(shù)據(jù)清洗與預(yù)處理·········································································184
4.3.1 檢測(cè)與處理缺失值 ·······························································185
4.3.2 檢測(cè)和處理重復(fù)值 ·······························································192
4.3.3 檢測(cè)和處理異常值 ·······························································197
4.3.4 數(shù)據(jù)轉(zhuǎn)換 ···········································································201
4.3.5 數(shù)據(jù)匹配 ···········································································213
4.3.6 數(shù)據(jù)標(biāo)準(zhǔn)化 ········································································218
4.4 數(shù)據(jù)處理與分析············································································221
4.4.1 層次化索引 ········································································222
4.4.2 數(shù)據(jù)連接與合并 ··································································234
4.4.3 數(shù)據(jù)聚合與分組運(yùn)算 ····························································245
4.5 時(shí)間序列分析···············································································261
4.5.1 時(shí)間序列基礎(chǔ) ·····································································261
4.5.2 時(shí)間戳( Timestamp) ···························································265
4.5.3 時(shí)區(qū)( Timezone) ·······························································274
4.5.4 時(shí)期( Period) ····································································277
4.5.5 時(shí)間差( Timedelta) ····························································283
4.5.6 時(shí)間序列重構(gòu) ·····································································285
4.6 Pandas 高級(jí)應(yīng)用 ···········································································302
4.6.1 分類數(shù)據(jù) ···········································································302
4.6.2 鏈?zhǔn)骄幊碳夹g(shù) ·····································································310
第 5 章 數(shù)據(jù)可視化—— Matplotlib·······························································315
5.1 繪圖基礎(chǔ)·····················································································315
5.2 二維圖形可視化············································································328
5.3 三維圖形可視化············································································354
5.4 使用動(dòng)畫·····················································································365
5.4.1 使用 Animation 模塊創(chuàng)建動(dòng)畫 ·················································365
5.4.2 使用 OpenGL 創(chuàng)建動(dòng)畫 ·························································373
5.5 復(fù)雜網(wǎng)絡(luò)結(jié)構(gòu)可視化······································································379
5.5.1 網(wǎng)絡(luò)可視化基礎(chǔ) ··································································380
5.5.2 網(wǎng)絡(luò)圖的生成 ·····································································385
5.5.3 網(wǎng)絡(luò)圖的繪制 ·····································································387