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# -*- coding: UTF-8 -*- import jieba.posseg import tensorflow as tf import pandas as pd import csv import math """ 1.必須獲取CSV文件夾(ID:文本) 2.返回(ID:分词后的文本) """ flags = tf.app.flags flags.DEFINE_string( "train_file_address" , "D:/NLPWORD/cut_word_test/hzytest.csv" , "添加训练数据文件" ) flags.DEFINE_string( "result_file_address" , "D:/NLPWORD/cut_word_test/hzytest_result.csv" , "生成结果数据文件" ) FLAGS = tf.app.flags.FLAGS def cut_word(train_data): """ 把数据按照行进行遍历,然后把结果按照行写在csv中 :return:分词结果list """ jieba.load_userdict( "newdict.txt" ) with open (FLAGS.result_file_address, "w" , encoding = 'utf8' ) as csvfile: writer = csv.writer(csvfile) for row in train_data.index: datas = train_data.loc[row].values[ 1 ] if isinstance (datas, str ) or not math.isnan(datas): words = jieba.posseg.cut(datas) line = '' for word in words: line = line + word.word + " " writer.writerow([train_data.loc[row].values[ 0 ], line]) def main(_): data = pd.read_csv(FLAGS.train_file_address) cut_word(data) if __name__ = = "__main__" : tf.app.run(main) |
以上这篇python处理csv中的空值方法就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/baidu_15113429/article/details/78615213