search for: sheet_nam

...is : I want read / write the excel sheet ( both xls / xlsx ) from Ruby , if you have any other solution also share with me .. *Source Code :* * * * bash-3.2$ cat rubyXL.rb require ''rubyXL'' workbook = RubyXL::Parser.parse("test.xlsx") workbook = RubyXL::Workbook.new sheet_Name = workbook.worksheets[0] puts sheet_Name * * * *ERROR* rubyXL.rb /usr/local/Cellar/ruby/2.0.0-p195/lib/ruby/site_ruby/2.0.0/rubygems/core_ext/kernel_require.rb:45:in *`require'': cannot load such file -- nokogiri (LoadError)* from /usr/local/Cellar/ruby/2.0.0-p195/lib/ruby/site_ruby/...

....xlsx file that has 46 sheets on it. I basically combined all 46 sheets > and read them as a single dataframe in R using package rio. > > I read a solution using package readlx, as suggested in a StackOverflow > discussion as follows: > df <- read_excel(path = filepath, sheet = sheet_name, guess_max = 100000). > Now, when you have so many sheets (46 in my case) in an Excel file, the rio > methodology is more practical. > > This is what I did: > path = > "C:/Users/myuser/Documents/DataScienceF/Forecast_and_Econometric_Analysis_FIGI > (4).xlsx" > fi...

...sheets on it. I basically combined all 46 sheets > > and read them as a single dataframe in R using package rio. > > > > I read a solution using package readlx, as suggested in a StackOverflow > > discussion as follows: > > df <- read_excel(path = filepath, sheet = sheet_name, guess_max = > 100000). > > Now, when you have so many sheets (46 in my case) in an Excel file, the > rio > > methodology is more practical. > > > > This is what I did: > > path = > > > "C:/Users/myuser/Documents/DataScienceF/Forecast_and_Econometr...

...> sheets > > and read them as a single dataframe in R using package rio. > > > > I read a solution using package readlx, as suggested in a > StackOverflow > > discussion as follows: > > df <- read_excel(path = filepath, sheet = sheet_name, guess_max = > 100000). > > Now, when you have so many sheets (46 in my case) in an Excel > file, the rio > > methodology is more practical. > > > > This is what I did: > > path = > > > "C:/Users/myuser/Doc...

...> > > and read them as a single dataframe in R using package rio. >> > > >> > > I read a solution using package readlx, as suggested in a >> StackOverflow >> > > discussion as follows: >> > > df <- read_excel(path = filepath, sheet = sheet_name, guess_max = >> > 100000). >> > > Now, when you have so many sheets (46 in my case) in an Excel file, >> the >> > rio >> > > methodology is more practical. >> > > >> > > This is what I did: >> > > path = >> &...

...ead them as a single dataframe in R using package rio. >>> > > >>> > > I read a solution using package readlx, as suggested in a >>> StackOverflow >>> > > discussion as follows: >>> > > df <- read_excel(path = filepath, sheet = sheet_name, guess_max = >>> > 100000). >>> > > Now, when you have so many sheets (46 in my case) in an Excel file, >>> the >>> > rio >>> > > methodology is more practical. >>> > > >>> > > This is what I did: >>...

The subject of your email is missing. Perhaps you need to read the Posting Guide (again?) about attachments. Embedding your example directly in the body of the email is generally more accessible in archives than attaching it. -- Sent from my phone. Please excuse my brevity. On April 27, 2016 1:14:17 PM GMT+01:00, G.Maubach at gmx.de wrote: >Hi All, > >I am addressing this post to all

Hi All, I am addressing this post to all who are new to R. When learing R in the last weeks I took some notes for myself to have code snippets ready for the data analysis process. I put these snippets together as a script template for future use. Almost all of the given command prototypes are tested. The template script contains snippets for best practices and leaves out the commands that

...rsion 4.3.2, and I have a .xlsx file that has 46 sheets on it. I basically combined all 46 sheets and read them as a single dataframe in R using package rio. I read a solution using package readlx, as suggested in a StackOverflow discussion as follows: df <- read_excel(path = filepath, sheet = sheet_name, guess_max = 100000). Now, when you have so many sheets (46 in my case) in an Excel file, the rio methodology is more practical. This is what I did: path = "C:/Users/myuser/Documents/DataScienceF/Forecast_and_Econometric_Analysis_FIGI (4).xlsx" figidat = import_list(path, rbind = TRUE)...