from sklearn.model_selection import train_test_split from sklearn.naive_bayes import MultinomialNB from sklearn.metrics import accuracy_score, classification_report # 划分训练集和测试集 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) # 初始化朴...
LEFT函数:从左边提取指定长度的文本; RIGHT函数:从右边提取指定长度的文本; MID函数:从文本指定位置提取指定长度的子文本。 Excel在365版本之中最新引入了一个强大的文本分割函数TEXTSPLIT函数。该函数能够根据文本对数据进行分割。分割结果以数组方式返回。 比如有这样一种情形,以往可以通过数据分列的方式对文本进行分割,...
from langchain.text_splitterimport(RecursiveCharacterTextSplitter,Language,)# Print a listofthe available languagesforcodeinLanguage:print(code)# The code to split python="""from langchain.document_loaders import PyPDFLoaderfrom langchain.text_splitter import RecursiveCharacterTextSplitterfrom transformers ...
print(df['post'].apply(lambda x: len(x.split(' '))).sum()) 10276752 这是该数据集包含的词数,接下来我们通过可视化来看看tags分布情况: my_tags = ['java','html','asp.net','c#','ruby-on-rails','jquery','mysql','php','ios','javascript','python','c','css','android','iphone'...
split(',') if len(terms) != 16: continue val = [int(i) for i in terms[1:]] data.append([terms[0], val]) return data if __name__ == '__main__': # model_type: support 'bert', 'albert', 'roberta', 'xlnet' # model_name: support 'bert-base-chinese', 'bert-base-...
clean_sentences=[remove_stopwords(r.split())forrinclean_sentences] 通过我们上面创建的词向量字典,clean_sentences将被用来构建句子的向量表示。 4.7 句子的向量表示 我们先取出句子中单词对应的词向量,每个词向量的维度是100维,将它们相加再取平均,得到的向量就用来表示这个句子。
1fromtkinterimport*23root =Tk()4text = Text(root,width=20,height=15)5text.pack()6defshow():7text.insert(INSERT,"i love python")8print(text.get("1.2", 1.6))9b1 = Button(text,text="点我",command=show)10text.window_create(INSERT,window=b1) ...
#Find the matching substrings in 2 strings. def utils_split_sentences(a, b): ## find clean matches match = difflib.SequenceMatcher(isjunk=None, a=a, b=b, autojunk=True) lst_match = [block for block in match....
split(): value = eval(expression) print(expression.rjust(30), '->', repr(value)) The output of Example 4-11 on GNU/Linux (Ubuntu 14.04) and OSX (Mavericks 10.9) is identical, showing that UTF-8 is used everywhere in these systems: $ python3 default_encodings.py locale.getpreferred...
import tkinter as tk root = tk.Tk() text = tk.Text(root, width=20, height=5) text.pack() text.insert("insert", "I love Python.com!") # 将任何格式的索引号统一为元组 (行,列) 的格式输出 def getIndex(text, index): return tuple(map(int, str.split(index, "."))) start = 1.0...