本文實例講述了Python讀取英文文件并記錄每個單詞出現(xiàn)次數(shù)后降序輸出。分享給大家供大家參考，具體如下：

對文中出現(xiàn)的句號，逗號和感嘆號做了相應(yīng)的處理

sorted排序函數(shù)用法：

按照value值降序排列：

sorted(dict.items(),key=lambda k:k[1],reverse=True)

按照value值升序排序：

sorted(dict.items(),key=lambda k:k[1],reverse=False)

或者

sorted(dict.items(),key=lambda k:k[1])

按照key值降序排列：

sorted(dict.items(),key=lambda k:k[0],reverse=True)

按照key值升序排列：

sorted(dict.items(),key=lambda k:k[0])

或者

sorted(dict.items(),key=lambda k:k[0],reverse=False)

Python示例：

# -*- coding:utf-8 -*-

#! python2

file_object=open("english.txt")

dict={}

for line in file_object:

line=line.replace(","," ")

line=line.replace("."," ")

line=line.replace("!"," ")

strs= line.split();

for str in strs:

if dict.has_key(str):

dict[str]+=1

else:

dict[str]=1

result=sorted(dict.items(),key=lambda k:k[1],reverse=True)

print result

english.txt文件：

We are busy all day, like swarms of flies without souls, noisy, restless, unable to hear the voices of the soul. As time goes by, childhood away, we grew up, years away a lot of memories, once have also eroded the bottom of the childish innocence, we regardless of the shackles of mind, indulge in the world buckish, focus on the beneficial principle, we have lost themselves.

運行結(jié)果：

[('the', 7), ('of', 6), ('we', 3), ('have', 2), ('away', 2), ('flies', 1), ('regardless', 1), ('restless', 1), ('up', 1), ('indulge', 1), ('mind', 1), ('all', 1), ('voices', 1), ('are', 1), ('in', 1), ('We', 1), ('busy', 1), ('shackles', 1), ('also', 1), ('memories', 1), ('by', 1), ('to', 1), ('unable', 1), ('goes', 1), ('themselves', 1), ('lot', 1), ('on', 1), ('buckish', 1), ('focus', 1), ('souls', 1), ('hear', 1), ('innocence', 1), ('world', 1), ('years', 1), ('day', 1), ('noisy', 1), ('a', 1), ('eroded', 1), ('grew', 1), ('like', 1), ('lost', 1), ('swarms', 1), ('bottom', 1), ('soul', 1), ('As', 1), ('without', 1), ('principle', 1), ('beneficial', 1), ('time', 1), ('childish', 1), ('childhood', 1), ('once', 1)]

PS：這里再為大家推薦2款相關(guān)統(tǒng)計工具供大家參考：

希望本文所述對大家Python程序設(shè)計有所幫助。

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