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HomeBackend DevelopmentPython TutorialExamples to explain how Python uses pandas to query data

查询和分析数据是pandas的重要功能,也是我们学习pandas的基础,下面这篇文章主要给大家介绍了关于Python数据分析之如何利用pandas查询数据的相关资料,文中通过示例代码介绍的非常详细,需要的朋友可以参考借鉴,下面来一起看看吧。

前言

在数据分析领域,最热门的莫过于Python和R语言,本文将详细给大家介绍关于Python利用pandas查询数据的相关内容,分享出来供大家参考学习,下面话不多说了,来一起看看详细的介绍吧。

示例代码

这里的查询数据相当于R语言里的subset功能,可以通过布尔索引有针对的选取原数据的子集、指定行、指定列等。我们先导入一个student数据集:


student = pd.io.parsers.read_csv('C:\\Users\\admin\\Desktop\\student.csv')

查询数据的前5行或末尾5行:


student.head()
student.tail()

查询指定的行:


student.ix[[0,2,4,5,7]] #这里的ix索引标签函数必须是中括号[]

查询指定的列:


student[['Name','Height','Weight']].head() #如果多个列的话,必须使用双重中括号

也可以通过ix索引标签查询指定的列:


student.ix[:,['Name','Height','Weight']].head()

查询指定的行和列:


student.ix[[0,2,4,5,7],['Name','Height','Weight']].head()

查询所有女生的信息:


student[student['Sex']=='F']

查询出所有12岁以上的女生信息:


student[(student['Sex']=='F') & (student['Age']>12)]

查询出所有12岁以上的女生姓名、身高和体重:


student[(student['Sex']=='F') & (student['Age']>12)][['Name','Height','Weight']]

上面的查询逻辑其实非常的简单,需要注意的是,如果是多个条件的查询,必须在&(且)或者|(或)的两端条件用括号括起来。

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