数据处理是数据科学模型开发流程的重要组成部分之一。数据科学家需要花费80％的时间准备数据集以使其适合建模。有时，对大型数据集执行数据整理和探索变得繁琐的工作，只有等待很长时间才能完成计算，或者转移到某些并行处理。
Pandas 是拥有大量API的著名 Python 库之一，但是在可伸缩性方面却失败了。对于大型数据集，迭代整个循环有时会花费很多时间，有时甚至是数小时，甚至对于小型数据集，使用标准循环对数据框架进行迭代也非常耗时。
在本文中，我们将讨论在大型数据集上加快迭代过程的技术或技巧。
1、Pandas 内置函数：iterrows()
iterrows() 是内置的 Pandas 库函数，它返回一系列的每个实例或行。它将数据帧作为一对索引和列特征作为Series进行迭代。
我使用了一个具有1000万条记录和5列的数据集。我们在数据集中使用字符串类型的特征"name"，必须将其删除以删除空格。
apply() 函数执行耗时「4.60秒」，比iterrows() 函数快427倍。
结论
在本文中，我们讨论了在Pandas数据帧上进行优化的几种技术，并比较了它们的时间复杂度。建议在非常特殊的情况下使用iterrows()函数。
可以轻松地从使用iterrows（）或索引方法转变为基于字典的迭代技术，该技术将工作流程的速度提高了77倍。Apply函数的速度提高了约400倍，但用途有限，人们需要对代码进行大量更改才能转换为这种方法。
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36)" data-darkmode-original-bgcolor-15882396318564="rgb(255, 255, 255)" data-darkmode-color-15882396318564="rgb(230, 230, 230)" data-darkmode-original-color-15882396318564="rgb(0, 0, 0)" data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(230, 230, 230)" data-darkmode-original-color-15900529136199="rgb(0, 0, 0)" style="max-width: 100%;letter-spacing: 0.544px;border-width: 0px;border-style: none;border-color: initial;box-sizing: border-box !important;overflow-wrap: break-word !important;"><section data-darkmode-bgcolor-15860613985508="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15860613985508="rgb(255, 255, 255)" data-darkmode-color-15860613985508="rgb(230, 230, 230)" data-darkmode-original-color-15860613985508="rgb(0, 0, 0)" data-darkmode-bgcolor-15870356070738="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15870356070738="rgb(255, 255, 255)" 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data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(230, 230, 230)" data-darkmode-original-color-15900529136199="rgb(0, 0, 0)" data-darkmode-bgimage-15900529136199="1" style="padding: 18px 15px 20px 10px;max-width: 100%;background-size: 100% 100%;background-image: url('https://www.zkxjob.com/wp-content/uploads/2022/07/wxsync-2022-07-a2a8a5e1e58f30392066a170034ee027.png');color: rgb(86, 146, 214);letter-spacing: 1.5px;background-repeat: no-repeat;box-sizing: border-box !important;overflow-wrap: break-word !important;"><section data-darkmode-bgcolor-15860613985508="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15860613985508="rgb(255, 255, 255)" data-darkmode-color-15860613985508="rgb(230, 230, 230)" data-darkmode-original-color-15860613985508="rgb(0, 0, 0)" data-darkmode-bgimage-15860613985508="1" data-darkmode-bgcolor-15870356070738="rgb(36, 36, 36)" 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data-darkmode-original-color-15882396318564="rgb(0, 0, 0)" data-darkmode-bgimage-15882396318564="1" data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(230, 230, 230)" data-darkmode-original-color-15900529136199="rgb(0, 0, 0)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;display: flex;justify-content: center;align-items: center;box-sizing: border-box !important;overflow-wrap: break-word !important;"><section data-darkmode-bgcolor-15860613985508="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15860613985508="rgb(255, 255, 255)" data-darkmode-color-15860613985508="rgb(230, 230, 230)" data-darkmode-original-color-15860613985508="rgb(0, 0, 0)" data-darkmode-bgimage-15860613985508="1" data-darkmode-bgcolor-15870356070738="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15870356070738="rgb(255, 255, 255)" data-darkmode-color-15870356070738="rgb(230, 230, 230)" data-darkmode-original-color-15870356070738="rgb(0, 0, 0)" data-darkmode-bgimage-15870356070738="1" data-darkmode-bgcolor-15870356071023="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15870356071023="rgb(255, 255, 255)" data-darkmode-color-15870356071023="rgb(230, 230, 230)" data-darkmode-original-color-15870356071023="rgb(0, 0, 0)" data-darkmode-bgimage-15870356071023="1" data-darkmode-bgcolor-15882384789136="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882384789136="rgb(255, 255, 255)" data-darkmode-color-15882384789136="rgb(230, 230, 230)" data-darkmode-original-color-15882384789136="rgb(0, 0, 0)" data-darkmode-bgimage-15882384789136="1" data-darkmode-bgcolor-15882396318564="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882396318564="rgb(255, 255, 255)" data-darkmode-color-15882396318564="rgb(230, 230, 230)" data-darkmode-original-color-15882396318564="rgb(0, 0, 0)" data-darkmode-bgimage-15882396318564="1" data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(230, 230, 230)" data-darkmode-original-color-15900529136199="rgb(0, 0, 0)" data-darkmode-bgimage-15900529136199="1" style="margin-left: 2px;max-width: 100%;width: 20px;box-sizing: border-box !important;overflow-wrap: break-word !important;"></section><section data-brushtype="text" data-darkmode-bgcolor-15860613985508="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15860613985508="rgb(255, 255, 255)" data-darkmode-color-15860613985508="rgb(51, 51, 51)" data-darkmode-original-color-15860613985508="rgb(51, 51, 51)" data-darkmode-bgimage-15860613985508="1" data-darkmode-bgcolor-15870356070738="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15870356070738="rgb(255, 255, 255)" data-darkmode-color-15870356070738="rgb(51, 51, 51)" data-darkmode-original-color-15870356070738="rgb(51, 51, 51)" data-darkmode-bgimage-15870356070738="1" data-darkmode-bgcolor-15870356071023="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15870356071023="rgb(255, 255, 255)" data-darkmode-color-15870356071023="rgb(51, 51, 51)" data-darkmode-original-color-15870356071023="rgb(51, 51, 51)" data-darkmode-bgimage-15870356071023="1" data-darkmode-bgcolor-15882384789136="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882384789136="rgb(255, 255, 255)" data-darkmode-color-15882384789136="rgb(51, 51, 51)" data-darkmode-original-color-15882384789136="rgb(51, 51, 51)" data-darkmode-bgimage-15882384789136="1" data-darkmode-bgcolor-15882396318564="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15882396318564="rgb(255, 255, 255)" data-darkmode-color-15882396318564="rgb(51, 51, 51)" data-darkmode-original-color-15882396318564="rgb(51, 51, 51)" data-darkmode-bgimage-15882396318564="1" data-darkmode-bgcolor-15900529136199="rgb(36, 36, 36)" data-darkmode-original-bgcolor-15900529136199="rgb(255, 255, 255)" data-darkmode-color-15900529136199="rgb(51, 51, 51)" data-darkmode-original-color-15900529136199="rgb(51, 51, 51)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;font-size: 14px;color: rgb(51, 51, 51);text-align: left;box-sizing: border-box !important;overflow-wrap: break-word !important;"><span style="max-width: 100%;font-family: 楷体, 楷体_GB2312, SimKai;white-space: pre-wrap;font-size: 12px;box-sizing: border-box !important;overflow-wrap: break-word !important;">点阅读原文,领AI全套资料！</span></section></section></section></section></section></section></section>本篇文章来源于: 菜鸟学Python
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