如何计算R中字符串中的单词数?
句子中的单词数可以用于文本分析,因此,我们需要对它们进行计数。这可以是单个句子或多个句子。我们可以使用strsplit和sapply查找一个句子或多个句子中的单词数。
示例
请看以下句子作为向量-
> x1<-c("Data Science is actually the Statistical analysis") > x1 [1] "Data Science is actually the Statistical analysis" > sapply(strsplit(x1, " "), length) [1] 7 > x2<-c("China faced trouble even after controlling COVID-19") > x2 [1] "China faced trouble even after controlling COVID-19" > sapply(strsplit(x2, " "), length) [1] 7 > x3<-c("Corona virus has changed everything in the world") > x3 [1] "Corona virus has changed everything in the world" > sapply(strsplit(x3, " "), length) [1] 8 > x4<-c("Corruption is the real threat to the success of any country") > x4 [1] "Corruption is the real threat to the success of any country" > sapply(strsplit(x4, " "), length) [1] 11 > x5<-c("Only unity of people can make lands prosper") > x5 [1] "Only unity of people can make lands prosper" > sapply(strsplit(x5, " "), length) [1] 8 > x6<-c("Small strings are easy to read", "Nobody likes large texts because it's boring", + "But the knowledge comes from reading") > x6 [1] "Small strings are easy to read" [2] "Nobody likes large texts because it's boring" [3] "But the knowledge comes from reading" > sapply(strsplit(x6, " "), length) [1] 6 7 6 > x7<-c("Quick Math questions are very simple to answer if you understand basic math calculations like division, percentage, ratio, etc.", + "It is a known fact that answering puzzles is not so easy but if you practice them then you will be able to build a base for solving puzzles.", + "Guesstimation Questions can be answered if you understand the right proxy about the context of the question.", + "Data extraction is the first step of programming in Data Science projects and SQL is highly required for this thing.", + "R programming and Python are widely used in Data Science. Both of these tools serve the same purpose that is analyzing large data sets.", + "Statistics is the base for Data Science and you must have a very good understanding of Statistics concepts to become a Data Scientist. + ", + "Machine Learning is a major part of Data Science projects. There are many machine learning algorithms that solve complex real-life problems in an easy way if applied correctly. + ", + "The main purpose of asking a tricky question is to check your critical thinking ability.", + "With the help probability, you can calculate whether you should do something or not. + ") > x7 [1] "Quick Math questions are very simple to answer if you understand basic math calculations like division, percentage, ratio, etc." [2] "It is a known fact that answering puzzles is not so easy but if you practice them then you will be able to build a base for solving puzzles." [3] "Guesstimation Questions can be answered if you understand the right proxy about the context of the question." [4] "Data extraction is the first step of programming in Data Science projects and SQL is highly required for this thing." [5] "R programming and Python are widely used in Data Science. Both of these tools serve the same purpose that is analyzing large data sets." [6] "Statistics is the base for Data Science and you must have a very good understanding of Statistics concepts to become a Data Scientist.\n" [7] "Machine Learning is a major part of Data Science projects. There are many machine learning algorithms that solve complex real-life problems in an easy way if applied correctly.\n" [8] "The main purpose of asking a tricky question is to check your critical thinking ability." [9] "With the help probability, you can calculate whether you should do something or not.\n" > sapply(strsplit(x7, " "), length) [1] 19 29 17 20 24 23 28 15 14