Pasar De Pdf A Excel En Mac
Gro Bert
someone sent me a feature table and taxonomy data in excel, is there a way to convert them into .qza file? so, I can do further analyses in QIIME2. I won't be able to get raw sequences data.
Many thanks.
Maggie
Hello!
Yeah, that's possible.
Step 1. Convert an excel file to tsv. I do not like to do this with excel software since it is often cause some issues. For me it is easier just copy the table from excel to Google sheet and download it as tsv (tab separated values).
Step 2. Make sure that your table formated properly. Just export any taxonomy.qza file as an tsv table and take a look on the format of the table. Or search for it on this forum.
Step 3. Import it to Qiime2. In this thread you can find example commands and format.
thank you.
I use Qiime2 via Galaxy. Does Galaxy have 'qiime2 tools import'? I only found 'qiime2 tools export'.
I tried to use 'qiime2 tools import' to covert .tsv into .qza.
(I converted the excel file to tsv via google sheet)
Could you post it as a new topic? It is already deviating from the initial one and in such way your question will gain more attention from other members with more experience with galaxy implementation.
Hello!
As I suggested above, you shloud submit it as a new question (new topic) on the forum since it is already different from the initial one, and moderators with more expirience with galaxy implementation will be able to help you.
As an alternative, you can install qiime2 on a local machine and then import the data to Qiime2 and use it on galaxy server.
I have situation where I have to convert all CSV in folder into excel files but data should be concatenated into one excel sheet. I want each individual converted into individual excel files.
let say for example I have 10 CSV files in Folder A. I want all these 10 files into 10 respective excel files. can you some please help me on this?
Please move your topic to the [KNIME Analytics Platform]. The KNIME Development is reserved for developing Knime itself, for example creating Knime nodes. Your question should be classified under the KNIME Analytics Platform.
Sorry for getting you confused. My Bad Not string in not printed in my sentences. I do not want all CSV files get concatenated into one singleexcel file. I want csv files are converted into excel files one file after another
Perfect world solution would be to download as excel and keep attachments. This would be the most preferred solution if there was a script or extension/app/block allowing to export a view to google sheets or to excel, so that it is still a spreadsheet data but with attachments loaded into the corresponding cells.
This process is the exact same for both Microsoft Excel 365 and Google Sheets, but here are example screenshots of how easy it is to search for records in Airtable and then send all of those records to Google Sheets with images intact:
Can someone help me on writing a C# code to convert the data from an excel file into byte array and then perform some validation check to the various columns in the excel like checking the date format, length of data, not null etc
The safest and the easiest way would be creating WebApi to handle converting the file into byte array and perform some validation. You can using third party libs like ClosedXML. In there you can convert excel file become c# POCO and do some validation. If the validation pass, then you can return byte array as result then your plugin can just use the value that already clean.
Why WebApi? Because it will help you to ease your development (no need doing merge) and will be more easy in the future if you want to upgrade to online version.
Thanks Braddev for your response. Converting the excel data into byte array was working with your code but how can i do validations on the value from the excel. For example, I have date of birth column in which I need to check the length of the value is 6 and if its 5 then add a '0' at the front and if it less than 5 or more than 6 just throw some error. How can I implement this.
x2mdate is not recommended. Use the datetime function instead, with the "excel" input argument, because it returns datetime values. For more information on updating your code, see Version History or Replace Discouraged Instances of Serial Date Numbers and Date Strings.
MATLABDate = x2mdate(ExcelDateNumber,Convention) converts an array of Excel serial date numbers to an array of MATLAB serial date numbers. It converts date numbers using either the 1900 date system or the 1904 date system, as specified by Convention.
The type of output is determined by an optional outputType input. If outputType is "datenum", then MATLABDate is an array of serial date numbers. If outputType is "datetime", then MATLABDate is a datetime array. By default, outputType is "datenum".
Due to a software limitation in Excel software, the year 1900 is considered a leap year. As a result, all DATEVALUEs reported by Excel software between Jan. 1, 1900 and Feb. 28, 1900 (inclusive) differs from the values reported by 1. For example:
Output date format, specified as "datenum" or "datetime". The output MATLABDate is in serial date format if "datenum" is specified or datetime format if "datetime" is specified. By default the output is in serial date format.
The type of output is determined by an optional outputType input argument. If outputType is "datenum", then MATLABDate is a serial date number. If outputType is "datetime", then MATLABDate is a datetime array. By default, outputType is "datenum".
There are no plans to remove x2mdate. However, the datetime function is recommended instead because it returns datetime values. The datetime data type provides flexible date and time formats, storage out to nanosecond precision, and properties to account for time zones and daylight saving time.
I would like to add a command at the end of a macro that exports all imageJ results into an excel spreadsheet and then do a basic calculation in the excel spreadsheet to add all central nuclei counts per fiber. A good example of what am trying to do is explained in this youtube video ( =M7R6qkdCdI0&t=47s)
If you are happy to do your own manual spreadsheet editing, post export-import, or macro-mediated results calculations, pre-export, then as @schmiedc pointed out, the existing Excel plugin or a regular .csv or .txt import-export may work fine for you.
Anyways, this is of minor concern for me at the moment. My major issue is that I am having trouble getting the macro to run in Batch mode. I have posted this on the forum, and am just wondering whether you could help me this too.
As far as I could tell, the major issue with the batch implementation before, was the macro needing to interact with the MorphoLibJ graphical user interface. My implementation gets around the problem by temporarily exiting batch mode. This work-around will be a little slower and require more computer resources than a purely batched alternative.
Maybe in general, check the above code against your own, just in-case I absent-mindedly changed something else. Hopefully now that you know the batching issue, you can even modify your own macro to get it working in that mode with the right c/n calculation.
Hi Antinos,
I actually managed to figure out what the issue was with the previous macro. Apparently, the macro was selecting the wrong image to analyse for Cnuclei counts after executing the the Imagecaluculator function.
Attached is the working version of that macro.
Finally, Is there a way to modify the macro to work in headless mode?
I may come back to this topic for my own development but I, currently, may not be the best person to help you implement exactly what you desire. I imagine others have already approached this topic. Perhaps this calls for a new forum post, specific to headless implementation? (and unless others are willing to chip-in here already).
As a data scientist or software engineer, you may find yourself needing to convert an XLSX file to a CSV file for analysis or to feed into another program. Python and Pandas make this task easy and efficient. In this tutorial, we will walk through the steps to convert an XLSX file to a CSV file using Pandas and then remove the index column.
Pandas is a popular Python library used for data manipulation and analysis. It provides data structures for efficiently storing and manipulating data, and tools for reading and writing data in a variety of formats, including CSV, Excel, SQL databases, and more.
By default, when you write a Pandas DataFrame to a CSV file using the to_csv() function, it includes the index column. However, you may not always want this column included in your output file. To remove the index column, you can simply set the index parameter to False, as shown above.
Converting an XLSX file to a CSV file using Python and Pandas is a simple and efficient process. The read_excel() and to_csv() functions make it easy to read in and write out data in a variety of formats, and the index parameter makes it easy to remove the index column from your output file. By following the steps outlined in this tutorial, you should be able to quickly convert XLSX files to CSV files and remove the index column as needed.
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