Missing values are commonly encountered when processing large collections of data. A missing value can correspond to an empty variable, an empty list, an empty dictionary, a missing element in a column, an empty dataframe, or even an invalid value. Defining empty variables and data structures is...
data = {'Amount':{'Apple':3,'Pear':2,'Strawberry':5},'Price':{'Apple':10,'Pear':9,'Strawberry':8}} df=DataFrame(data)print(df)
例子 # declaring an empty data framedata_frame1<-data.frame(col1=NA,col2=NA,col3=NA,col4=NA)[numeric(0),]# printing data frameprint("Data Frame :")print(data_frame1) Bash Copy 输出 [1]“DataFrame:“[1]col1 col2 col3 col4<0rows>(or0-length row.names) Bash Copy 方法2:以NU...