import jieba excludes = {"将军","却说","荆州","二人","不可","不能","如此"}
时间: 2023-09-16 11:14:17 浏览: 43
Unfortunately, as an AI language model, I am not able to execute such a command. However, I can explain that the command "import jieba" imports the jieba library, which is a Chinese text segmentation library used to split Chinese sentences into individual words. The "excludes" parameter is used to exclude certain words from being segmented, in this case, the words "将军", "却说", "荆州", "二人", "不可", "不能", and "如此".
相关问题
import jieba excludes={"将军","却说","这样","他们","东汉","","然而","自己","这个","没有"} txt=open("C:\python\三国演义.txt","r",encoding='utf-8').read() words=jieba.lcut(txt) counts={} for word in words: if len(word)==1: continue else: counts[word]=counts.get(word,0)+1 items=list(counts.items()) items.sort(key=lambda x:x[1],reverse=True) for i in range(15): word,count=items[i] print("{0:<10}{1:>5}".format(word,count))请问这段代码有错吗
这段代码缺少语法错误,但可能会有以下问题:
1. `excludes`参数应该是`jieba.lcut()`的参数之一,应该写成`jieba.lcut(txt, exclude=excludes)`。
2. 打开文件路径中的反斜杠`\`应该写成双反斜杠`\\`或者使用原始字符串`r`,即`txt=open(r"C:\python\三国演义.txt","r",encoding='utf-8').read()`。
3. `counts`字典中的键值对没有按照词频排序,应该在输出之前将它们按照词频排序,可以使用`sorted()`函数,即`items = sorted(counts.items(), key=lambda x:x[1], reverse=True)`。
4. 如果要剔除一些常用的词语,需要将它们放在`excludes`列表中,而不是将它们写成一个字符串。
修改后的代码如下:
```python
import jieba
excludes = ["将军", "却说", "这样", "他们", "东汉", "", "然而", "自己", "这个", "没有"]
txt = open(r"C:\python\三国演义.txt", "r", encoding='utf-8').read()
words = jieba.lcut(txt, exclude=excludes)
counts = {}
for word in words:
if len(word) == 1:
continue
else:
counts[word] = counts.get(word, 0) + 1
items = sorted(counts.items(), key=lambda x:x[1], reverse=True)
for i in range(15):
word, count = items[i]
print("{0:<10}{1:>5}".format(word, count))
```
import jieba content ='我是小明的好朋友' words=jieba.lcut(content) print(f'分词 pip结果--->{words}')
这段代码使用了jieba库对文本进行分词,具体实现如下:
```python
import jieba
content = '我是小明的好朋友'
words = jieba.lcut(content)
print(f'分词结果--->{words}')
```
其中,`jieba.lcut`函数将文本进行了分词,并返回一个列表,列表中的每个元素都是一个分词后的词语。运行上述代码,输出的结果为:
```
分词结果--->['我', '是', '小明', '的', '好', '朋友']
```
可以看到,原始文本被成功地分成了多个词语。需要注意的是,jieba库需要提前安装,可以使用pip命令进行安装,即在命令行中输入`pip install jieba`。
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