标签：
标签云是现在大数据里面最喜欢使用的一种展现方式，其中在python3下也能实现标签云的效果，贴图如下：
-------------------进入正文---------------------
首先要安装以下几个库：
1 #!/usr/bin/python3.4 2 # -*- coding: utf-8 -*- 3 4 # http://www.lfd.uci.edu/~gohlke/pythonlibs/#cx_freeze 5 # 万能仓库下载pygame 6 # pip3下载simplejson
还有最重要的库：
pip3 install pytagcloud
或者去官网下载：
https://pypi.python.org/pypi/pytagcloud/
安装完毕，利用官网的例子来做：
1 from pytagcloud import create_tag_image, make_tags 2 from pytagcloud.lang.counter import get_tag_counts 3 4 YOUR_TEXT = "A tag cloud is a visual representation for text data, typically5 used to depict keyword metadata on websites, or to visualize free form text." 6 7 tags = make_tags(get_tag_counts(YOUR_TEXT), maxsize=120) 8 9 create_tag_image(tags, ‘cloud_large.png‘, size=(900, 600), fontname=‘Lobster‘)
果断报错：
Traceback (most recent call last):
File "D:/code/pythonwork/Text.py", line 96, in <module>
tags = make_tags(get_tag_counts(YOUR_TEXT), maxsize=120)
File "C:\Python34\lib\site-packages\pytagcloud\lang\counter.py", line 25, in get_tag_counts
return sorted(counted.iteritems(), key=itemgetter(1), reverse=True)
AttributeError: ‘dict‘ object has no attribute ‘iteritems‘
看了发现问题出在库中的：
# counter.py return sorted(counted.iteritems(), key=itemgetter(1), reverse=True)
原来是python3.4不支持写法：
在Python2.x中，items( )用于 返回一个字典的拷贝列表【Returns a copy of the list of all items (key/value pairs) in D】，占额外的内存。
iteritems() 用于返回本身字典列表操作后的迭代【Returns an iterator on all items(key/value pairs) in D】，不占用额外的内存。
Python 3.x 里面，iteritems() 和 viewitems() 这两个方法都已经废除了，而 items() 得到的结果是和 2.x 里面 viewitems() 一致的。在3.x 里 用 items()替换iteritems() ，可以用于 for 来循环遍历。
但是当我换成：
# counter.py return sorted(counted.items(), key=itemgetter(1), reverse=True)
发现运行并没有错误，但是没有生成标签云啊，一遍一遍打印出来，终于找到问题了：
from pytagcloud import create_tag_image
这个是为了生成一个元组的东西：
# counts =[(‘cloud‘, 3),
# (‘words‘, 2),
# (‘code‘, 1),
# (‘word‘, 1),
# (‘appear‘, 1)]
但是python3里面的items()是达不到这个效果的，所以我就自己写吧。
读取txt文件，将每一行都按照空格划分成一个个数组的元素：
1 arr = [] 2 file = open(‘../tagcloud/tag_file.txt‘, ‘r‘) 3 data = file.read().split(‘\r\n‘) 4 for content in data: 5 contents = validatecontent(content).split() 6 for word in contents: 7 arr.append(word)
[‘BAISC‘, ‘Python‘, ‘BASICA‘, ‘GVBASIC‘, ‘GWBASIC‘, ‘Python‘, ‘ETBASIC‘, ‘QBASIC‘, ‘Quick‘, ‘Basic‘, ‘Turbo‘, ‘Basic‘, ‘True‘, ‘Python‘, ‘java‘, ‘Basic‘, ‘Visual‘, ‘Basic‘, ‘Visual‘, ‘Basic‘, ‘Net‘, ‘Power‘, ‘Basic‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘Small‘, ‘Basic‘, ‘Free‘, ‘Basic‘, ‘DarkBASIC‘, ‘VBScript‘, ‘Visual‘, ‘Basic‘, ‘For‘, ‘ApplicationsVBA‘, ‘REALbasic‘, ‘C‘, ‘C‘, ‘Turbo‘, ‘C‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘PHP‘, ‘HTML‘, ‘Borland‘, ‘C‘, ‘C‘, ‘Builder‘, ‘CCLI‘, ‘Python‘, ‘java‘, ‘ObjectiveC‘, ‘C#‘, ‘Microsoft‘, ‘Visual‘, ‘C‘, ‘Pascal‘, ‘Delphi‘, ‘Turbo‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘PHP‘, ‘HTML‘, ‘Pascal‘, ‘Object‘, ‘Pascal‘, ‘Free‘, ‘Pascal‘, ‘Lazarus‘, ‘FORTRAN‘, ‘MATLAB‘, ‘Scilab‘, ‘GNU‘, ‘Octave‘, ‘R‘, ‘SPlus‘, ‘Mathematica‘, ‘Maple‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘PHP‘, ‘HTML‘, ‘Julia‘, ‘xBaseClipper‘, ‘Visual‘, ‘FoxPro‘, ‘SQLPLSQL‘, ‘TSQL‘, ‘SQLPSM‘, ‘LINQ‘, ‘Xquer‘, ‘Lua‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘Perl‘, ‘PHP‘, ‘Python‘, ‘Ruby‘, ‘ASP‘, ‘JSP‘, ‘TclTk‘, ‘VBScript‘, ‘AppleScript‘, ‘AAuto‘, ‘ActionScript‘, ‘DMDScript‘, ‘ECMAScript‘, ‘JavaScript‘, ‘JScript‘, ‘TypeScript‘, ‘sh‘, ‘bash‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘PHP‘, ‘HTML‘, ‘sed‘, ‘awk‘, ‘PowerShell‘, ‘csh‘, ‘tcsh‘, ‘ksh‘, ‘zsh‘, ‘XMLSVG‘, ‘XML‘, ‘Schema‘, ‘Python‘, ‘java‘, ‘XSLT‘, ‘XHTML‘, ‘MathML‘, ‘XAML‘, ‘SSML‘, ‘SGML‘, ‘HTML‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘Curl‘, ‘SVG‘, ‘XML‘, ‘Schema‘, ‘XSLT‘, ‘XHTML‘, ‘MathML‘, ‘XAML‘, ‘SSML‘, ‘Java‘, ‘Jython‘, ‘JRuby‘, ‘JScheme‘, ‘Groovy‘, ‘Kawa‘, ‘Scala‘, ‘Clojure‘, ‘ALGOL‘, ‘APLJ‘, ‘Ada‘, ‘Falcon‘, ‘Forth‘, ‘Io‘, ‘MUMPS‘, ‘PLI‘, ‘PostScript‘, ‘REXX‘, ‘SAC‘, ‘Self‘, ‘Simula‘, ‘Swift‘, ‘IronPython‘, ‘IronRuby‘, ‘COBOL‘, ‘Python‘, ‘java‘, ‘SQL‘, ‘VB‘, ‘PHP‘, ‘HTML‘]
对每一个元素都来个计数：
from collections import Counter counts = Counter(arr).items() print(counts)
效果出来了：
dict_items([(‘For‘, 1), (‘SQL‘, 8), (‘JRuby‘, 1), (‘Builder‘, 1), (‘HTML‘, 6), (‘LINQ‘, 1), (‘BAISC‘, 1), (‘BASICA‘, 1), (‘PHP‘, 6), (‘Octave‘, 1), (‘csh‘, 1), (‘PostScript‘, 1), (‘awk‘, 1), (‘Ruby‘, 1), (‘AppleScript‘, 1), (‘Object‘, 1), (‘java‘, 11), (‘TclTk‘, 1), (‘Xquer‘, 1), (‘ksh‘, 1), (‘zsh‘, 1), (‘ETBASIC‘, 1), (‘AAuto‘, 1), (‘Borland‘, 1), (‘SVG‘, 1), (‘Jython‘, 1), (‘Simula‘, 1), (‘IronPython‘, 1), (‘Python‘, 14), (‘Microsoft‘, 1), (‘ActionScript‘, 1), (‘XHTML‘, 2), (‘REXX‘, 1), (‘COBOL‘, 1), (‘Scilab‘, 1), (‘Ada‘, 1), (‘Basic‘, 9), (‘GVBASIC‘, 1), (‘ECMAScript‘, 1), (‘TypeScript‘, 1), (‘Falcon‘, 1), (‘Clojure‘, 1), (‘ASP‘, 1), (‘ALGOL‘, 1), (‘XMLSVG‘, 1), (‘GWBASIC‘, 1), (‘VBScript‘, 2), (‘CCLI‘, 1), (‘Lazarus‘, 1), (‘Julia‘, 1), (‘JSP‘, 1), (‘PowerShell‘, 1), (‘IronRuby‘, 1), (‘Power‘, 1), (‘FORTRAN‘, 1), (‘Self‘, 1), (‘Perl‘, 1), (‘Small‘, 1), (‘FoxPro‘, 1), (‘REALbasic‘, 1), (‘GNU‘, 1), (‘Mathematica‘, 1), (‘True‘, 1), (‘Visual‘, 5), (‘JScheme‘, 1), (‘Maple‘, 1), (‘Quick‘, 1), (‘Turbo‘, 3), (‘SAC‘, 1), (‘JScript‘, 1), (‘APLJ‘, 1), (‘sh‘, 1), (‘Kawa‘, 1), (‘Pascal‘, 4), (‘TSQL‘, 1), (‘SPlus‘, 1), (‘C‘, 6), (‘xBaseClipper‘, 1), (‘tcsh‘, 1), (‘SQLPSM‘, 1), (‘ApplicationsVBA‘, 1), (‘SSML‘, 2), (‘R‘, 1), (‘Groovy‘, 1), (‘XSLT‘, 2), (‘MUMPS‘, 1), (‘bash‘, 1), (‘DarkBASIC‘, 1), (‘SGML‘, 1), (‘XAML‘, 2), (‘VB‘, 8), (‘Curl‘, 1), (‘Schema‘, 2), (‘MATLAB‘, 1), (‘MathML‘, 2), (‘Lua‘, 1), (‘Net‘, 1), (‘ObjectiveC‘, 1), (‘JavaScript‘, 1), (‘Java‘, 1), (‘Io‘, 1), (‘Free‘, 2), (‘Delphi‘, 1), (‘sed‘, 1), (‘XML‘, 2), (‘Forth‘, 1), (‘C#‘, 1), (‘SQLPLSQL‘, 1), (‘QBASIC‘, 1), (‘DMDScript‘, 1), (‘Swift‘, 1), (‘Scala‘, 1), (‘PLI‘, 1)])
最后直接代入进去就行了：
1 tags = make_tags(counts, maxsize=120) 2 3 create_tag_image(tags, ‘cloud_large.png‘, size=(900, 600), fontname=‘Lobster‘)
具体的修正需要自己慢慢去琢磨了，比如文字大小、图片大小、背景颜色等等。
到这里标签云是算完成了的，但是却是不支持中文，原因是没有合适的ttf字体文件，准备一个 ttf 中文字体，如 simhei.ttf或者MicrosoftYaHei.ttf ，将其移动到
# C:\Python34\Lib\site-packages\pytagcloud\fonts
{
"name": "MicrosoftYaHei",
"ttf": "MicrosoftYaHei.ttf",
"web": "none"
}
注意前后的逗号就行。最后将这里的代码改一下：
create_tag_image(tags, ‘cloud_large.png‘, size=(900, 600), fontname=‘MicrosoftYaHei‘)
运行，搞定！中文效果图：
我的在github里面，可以去下载看看。
标签：
原文地址：http://www.cnblogs.com/TTyb/p/5850540.html
