When we are reading an article or even a novel, we want to know which word appears the most in the text and how many times it appears. What should we do? Python can do this job with simple code. You can also expand a bit and infer who the protagonist is by whose name or which sentence appears most often in the novel? What's the mantra? Isn’t it very interesting? Come and try it.
Idea:
is to first extract each character and put it in the list;
then filter Remove the punctuation marks;
Finally, use a dictionary to accumulate the frequency of a certain word.
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Take the novel Youth as an example:
#coding:utf-8
word_lst = []
word_dict = {}
exclude_str = "，。！？、（）【】<>《》=：+-*—“”…"
with open("芳华.txt","r") as fileIn ,open("芳华字频.txt",'w') as fileOut:
# 添加每一个字到列表中
for line in fileIn:
for char in line:
word_lst.append(char)
# 用字典统计每个字出现的个数
for char in word_lst:
if char not in exclude_str:
if char.strip() not in word_dict: # strip去除各种空白
word_dict[char] = 1
else :
word_dict[char] += 1
# 排序
# x[1]是按字频排序，x[0]则是按字排序
lstWords = sorted(word_dict.items(), key=lambda x:x[1], reverse=True)
# 输出结果 (前100)
print ('字符\t字频')
print ('=============')
for e in lstWords[:100]:
print ('%s\t%d' % e)
fileOut.write('%s, %d\n' % e)Output results
字符 字频 ============= 的 3641 一 1834 了 1748 是 1506 不 1267 我 1229 她 1156 他 985 小 962 个 921 人 866 在 853 刘 745 丁 728 那 723 上 705 来 698 峰 691 们 684 就 667 说 577 有 572 到 564 这 562 里 537 儿 520 嫚 499 子 494 都 492 着 491 大 482 么 462 出 460 看 441 也 415 得 404 下 383 时 367 还 366 女 349 地 340 头 331 好 327 没 326 去 321 过 320 老 317 跟 311 你 309 把 307 对 303 年 301 会 300 生 291 为 289 发 289 要 281 何 280 亲 273 后 272 给 267 和 266 天 265 家 259 手 251 长 251 想 249 多 242 自 241 开 240 当 236 兵 235 样 232 郝 230 可 228 起 225 被 224 成 216 十 215 什 215 以 209 事 209 从 209 点 208 能 203 两 203 回 202 门 201 所 195 淑 188 雯 188 只 188 心 184 身 184 让 179 道 179 母 174 做 173 话 173 最 172 >>>
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