merge

问题 my studies project is to develop a neural network to recognize text on license plates. Therefore, I found the ReId-dataset at https://medusa.fit.vutbr.cz/traffic/research-topics/general-traffic-analysis/holistic-recognition-of-low-quality-license-plates-by-cnn-using-track-annotated-data-iwt4s-avss-2017/. This dataset contains a bunch of images of number plates as well as the text of the license plates and was used by Spanhel et al. for a similar approach as the one I have in mind. Example of

问题 I already saw variants of my problem under how-to-merge-two-xml-files-with-xslt or how-can-i-merge-these-two-xml-files-using-xslt , but these examples do not handle the text-output and also not handle a static refernece to'default.xml'. I am trying to generate a C headerfile beeing generated from a defaults.xml that gets amended by an target.xml. I am using xsltproc as xslt processor and would like to be able to do xslproc merg.xsl target1.xml > target1.h . Meaning to have one defaults.xml

问题 I already saw variants of my problem under how-to-merge-two-xml-files-with-xslt or how-can-i-merge-these-two-xml-files-using-xslt , but these examples do not handle the text-output and also not handle a static refernece to'default.xml'. I am trying to generate a C headerfile beeing generated from a defaults.xml that gets amended by an target.xml. I am using xsltproc as xslt processor and would like to be able to do xslproc merg.xsl target1.xml > target1.h . Meaning to have one defaults.xml

问题 I'm trying to merge some data between a single List of dictionaries that has lists inside. Merging would happen based on the "object" key if they matched. Also adding to their given "section" if the same value was matched. Given the following data: data = [ { "semver":"1.0.0", "sections":[ { "name":"Add", "messages":[ "add: comment here" ] } ], "object":"files.sh" }, { "semver":"1.0.0", "sections":[ { "name":"Add", "messages":[ "add: Second comment here" ] } ], "object":"files.sh" }, {

问题 Say I have a dataframe df , and a directory ./ which has the following excel files inside: path = './' for root, dirs, files in os.walk(path): for file in files: if file.endswith(('.xls', '.xlsx')): print(os.path.join(root, file)) # dfs.append(read_dfs(os.path.join(root, file))) # df = reduce(lambda left, right: pd.concat([left, right], axis = 0), dfs) Out: df1.xlsx, df2.xlsx, df3.xls ... I want to merge df with all files from path based on common columns date and city . It works with the

问题 I want to merge two data frames on Date Time column dtype.date-time columns contain both similar and different values. But I am unable to merge them such that all unique date-time rows are finally there..with NA in uncommon columns. I am getting NAs in date_time column for 2nd data frame. tried both in R and python python code: df=pd.merge(df_met, df_so2, how='left', on='Date_Time') In R..data_type is date-time using as.POSIXct df_2<-join(so2, met_km, type="inner") df3 <- merge(so2, met_km,

问题 I would like to merge 2 data frames based on multiple conditions. DF1 <- data.frame("col1" = rep(c("A","B"), 18), "col2" = rep(c("C","D","E"), 12), "value"= (sample(1:100,36)), "col4" = rep(NA,36)) DF2 <- data.frame("col1" = rep("A",6), "col2" = rep(c("C","D"),3), "data" = rep(c(1,3),3), "min" = seq(0,59,by=10), "max" = seq(10,69,by=10)) > DF1 col1 col2 value col4 1 A C 22 NA 2 B D 58 NA 3 A E 35 NA 4 B C 86 NA 5 A D 37 NA 6 B E 16 NA 7 A C 46 NA 8 B D 23 NA 9 A E 88 NA 10 B C 3 NA 11 A D 33

问题 I would like to merge 2 data frames based on multiple conditions. DF1 <- data.frame("col1" = rep(c("A","B"), 18), "col2" = rep(c("C","D","E"), 12), "value"= (sample(1:100,36)), "col4" = rep(NA,36)) DF2 <- data.frame("col1" = rep("A",6), "col2" = rep(c("C","D"),3), "data" = rep(c(1,3),3), "min" = seq(0,59,by=10), "max" = seq(10,69,by=10)) > DF1 col1 col2 value col4 1 A C 22 NA 2 B D 58 NA 3 A E 35 NA 4 B C 86 NA 5 A D 37 NA 6 B E 16 NA 7 A C 46 NA 8 B D 23 NA 9 A E 88 NA 10 B C 3 NA 11 A D 33

问题 I have a df which contains my main data which has one million rows . My main data also has 30 columns . Now I want to add another column to my df called category . The category is a column in df2 which contains around 700 rows and two other columns that will match with two columns in df . I begin with setting an index in df2 and df that will match between the frames, however some of the index in df2 doesn't exist in df . The remaining columns in df2 are called AUTHOR_NAME and CATEGORY . The

问题 I have a df which contains my main data which has one million rows . My main data also has 30 columns . Now I want to add another column to my df called category . The category is a column in df2 which contains around 700 rows and two other columns that will match with two columns in df . I begin with setting an index in df2 and df that will match between the frames, however some of the index in df2 doesn't exist in df . The remaining columns in df2 are called AUTHOR_NAME and CATEGORY . The