交通時空大數據分析、挖掘與可視化（Python版）
餘慶，李瑋峰
- 出版商: 清華大學
- 出版日期: 2022-09-01
- 定價: $1,014
- 售價: 8.5 折 $862
- 語言: 簡體中文
- ISBN: 7302611963
- ISBN-13: 9787302611967
-
相關分類:
大數據 Big-data、Data Science
下單後立即進貨 (約4週~6週)
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目錄大綱
目 錄
基 礎 篇
第1章 緒論 ·····························2
1.1 多源交通時空大數據簡介 ················2
1.1.1 傳統集計統計數據 ·······························3
1.1.2 個體連續追蹤數據 ·······························4
1.1.3 地理空間信息數據 ·······························5
1.2 為什麽要用Python處理交通大數據 ·····6
1.2.1 常用數據處理技術 ·······························6
1.2.2 Python在交通大數據領域中的優勢 ····8
1.2.3 Python與SQL的比較 ····························9
1.3 大規模數據處理的解決方案··············9
1.3.1 決定大數據處理性能的三個硬件
要素 ·······················································9
1.3.2 分佈式數據處理架構 ·························11
1.4 本章習題 ···································14
第2章 Python數據處理基礎 ······15
2.1 Python的環境配置 ························15
2.1.1 Python的集成開發環境 ······················15
2.1.2 Anaconda的安裝 ·································16
2.1.3 Jupyter Notebook的使用 ·····················16
2.1.4 Python第三方庫的安裝 ······················18
2.2 Python基本語法 ···························19
2.2.1 對象與變量 ·········································19
2.2.2 運算符 ·················································20
2.2.3 內置數據類型 ·····································20
2.2.4 語句 ·····················································24
2.2.5 函數 ·····················································26
2.2.6 包的使用 ·············································27
2.2.7 數據分析常用第三方庫簡介 ·············28
2.3 pandas數據處理基礎 ·····················29
2.3.1 數據文件的編碼格式與存儲形式 ·····30
2.3.2 數據表的行列處理 ·····························33
2.3.3 數據的表格運算 ·································41
2.4 時空大數據的處理思維 ·················46
2.4.1 復雜數據處理任務的解決思路 ·········46
2.4.2 數據處理任務分解實例：地鐵換乘量
識別 ······················································49
2.5 數據處理中表格運算的常用技巧 ······51
2.5.1 分組編號 ·············································51
2.5.2 去除重復的記錄 ·································53
2.5.3 個體ID重新編號 ·································54
2.5.4 生成數據之間的對應表 ·····················55
2.5.5 時空插值 ·············································58
2.6 本章習題 ···································60
2.6.1 思考題 ·················································60
2.6.2 Python基礎代碼練習 ··························60
2.6.3 pandas基礎代碼練習 ··························62
第3章 數據可視化基礎 ············64
3.1 可視化的基本原則 ·······················64
