Python处理非结构化数据 Python阅读HTML页面 Python Word Tokenization 已经以行和列格式存在的数据或者可以很容易地转换为行和列的数据,以便稍后它可以很好地适合数据库,这被称为结构化数据。例如CSV,TXT,XLS文件等。这些文件有一个分隔符,固定宽度或可变宽度,其中缺失值在分隔符之间表示为空白。但有时候我们会得到这些行不是固定宽度的数据,或者它们只是HTML,图像或pdf文件。这些数据被称为非结构化数据。尽管可以通过处理HTML标签来处理HTML文件,但是来自Twitter的提要或来自新闻提要的纯文本文档可以在不具有分隔符的情况下不具有要处理的标签。在这种情况下,我们使用来自各种python库的不同内置函数来处理文件。 读取数据 在下面的例子中,我们获取一个文本文件并读取文件,将文件中的每一行分隔开来。接下来我们可以将输出分成更多的行和单词。原始文件是一个包含描述Python语言的段落的文本文件。 filename = 'path\input.txt' with open(filename) as fn: # Read each line ln = fn.readline() # Keep count of lines lncnt = 1 while ln: print("Line {}: {}".format(lncnt, ln.strip())) ln = fn.readline() lncnt += 1 当我们执行上面的代码时,它会产生以下结果。 Line 1: Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. It provides constructs that enable clear programming on both small and large scales. Line 2: Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library. Line 3: Python interpreters are available for many operating systems. CPython, the reference implementation of Python, is open source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation. 计数字频率 我们可以使用计数器函数来计算文件中文字的频率,如下所示。 from collections import Counter with open(r'pathinput2.txt') as f: p = Counter(f.read().split()) print(p) 当我们执行上面的代码时,它会产生以下结果。 Counter({'and': 3, 'Python': 3, 'that': 2, 'a': 2, 'programming': 2, 'code': 1, '1991,': 1, 'is': 1, 'programming.': 1, 'dynamic': 1, 'an': 1, 'design': 1, 'in': 1, 'high-level': 1, 'management.': 1, 'features': 1, 'readability,': 1, 'van': 1, 'both': 1, 'for': 1, 'Rossum': 1, 'system': 1, 'provides': 1, 'memory': 1, 'has': 1, 'type': 1, 'enable': 1, 'Created': 1, 'philosophy': 1, 'constructs': 1, 'emphasizes': 1, 'general-purpose': 1, 'notably': 1, 'released': 1, 'significant': 1, 'Guido': 1, 'using': 1, 'interpreted': 1, 'by': 1, 'on': 1, 'language': 1, 'whitespace.': 1, 'clear': 1, 'It': 1, 'large': 1, 'small': 1, 'automatic': 1, 'scales.': 1, 'first': 1}) Python阅读HTML页面 Python Word Tokenization