I have a webservice which continuously generate/update a csv file which can be downloaded externally. I would like to use an Excel file to continuously get the content of the csv file, and do calculation and visualization accordingly.
e.g.
my csv file contains 4 rows, 3 columns.
In an Excel sheet, A1:C4 are used to store the contents of the csv file. A5:C5 are the average of each column. And a bar chart of the contents in each column is displayed in A5.
How can I ask the Excel to download the csv file by specifying its URL, and store in A1:C4? And how to make it automatically update its contents when the csv file is updated?
Related
When converting an excel file to csv in synapse pipeline or dataflow, I need to put the values of certain cells in excel in an additional column.
I was able to convert an excel file to csv, but I can't figure out how to read the values in a particular cell and add them as a column.
What I would like to achieve is as follows.
Excel sample file
I want to add "outlet_code" as a column in the "C2" cell of the Excel file.
csv file
you can try the below logic:
1st use a copy activity to copy the content of the Excel file from A1 to c2 into CSV (assuming the place of the code remains the same)
Excel Source dataset :
Leverage Lookup Activity to get the code value
Lookup should map to the CSV file generated above
Create another Copy activity to actually copy your excel content into CSV with the current setting you have and a below logic to add an additional column :
Add additional column in copy activity using Azure Data Factory
We got a measuring device thats connected to a CSV file. Whenever we measure a product the CSV get's updated.
This CSV file is then connected to a excel file to make it user friendly and to add comments. So the CSV file is connected and displayed in a table. We added another column to this table to put a comment.
The problem is when we the csv file updates (new row) the comment of the last row goes down to the new row.
Example: The digits come from the CSV file, and the ok is added manually.
When we refresh the workbook so the new row gets added we get the following result:
The ok from row 2 goes down to new row.
It should be like this:
Is there a way to save/stuck the manually added value to a row?
I have question
There are excel data like this
input file
More than 500 person
I wanna convert data to csv
expected csv result
The data age is not 100% the second row, some may be third row. Name can be duplicate data.
I’m really confused. Can i use excel feature to do this or any way like coding?
I upload file : https://ufile.io/rxe1l
Add name, age, add etc as column in excel and export as .csv.
In your Excel workbook, switch to the File tab, and then click Save As. Alternatively, you can press F12 to open the same Save As dialog.
In the Save as type box, choose to save your Excel file as CSV (Comma delimited).
Please simply follow this link conversation excel into csv
Using the Paraview application, I would like to extract data from a .vtk unstructured grid file and convert this data into .txt or .csv files. In the file menu, I have tested Save Data but I obtain a .csv file with one column "Cell Type" containing only the value 9. How can I get the data in a .txt or .csv file ? My .vtk file contains 9 variables and for each variable, I have data at each time step.
Looks like your dataset contains only PointsData, not CellData. Make sure to Select :
"Point Association : Point"
when saving the data as a .csv file.
How can I save data from an Excel sheet to .RData file in R? I want to use one of the packages in R and to load my dataset as data(dataset) i think i have to save the data as .RData file and then load that into the package. My data currently is in an Excel spreadsheet.
my excel sheets has column names like x, y , time.lag.
I have saved it as .csv
then i use:
x=read.csv('filepath', header=T,)
then i say
data(x)
and it shows dataset 'x' not found
There are also several packages that allow directly reading from XLS and XLSX files. We've even had a question on that topic here and here for example. However you decide to read in the data, saving into an RData can be handled with save, save.image, saveRDS and probably some others I'm not thinking about.
save your Excel data as a .csv file and import it using read.csv() or read.table().
Help on each will explain the options.
For example, you have a file called myFile.xls, save it as myFile.csv.
library(BBMM)
# load an example dataset from BBMM
data(locations)
# from the BBMM help file
BBMM <- brownian.bridge(x=locations$x, y=locations$y, time.lag=locations$time.lag[-1], location.error=20, cell.size=50)
bbmm.summary(BBMM)
# output of summary(BBMM)
Brownian motion variance : 3003.392
Size of grid : 138552 cells
Grid cell size : 50
# subsitute locations for myData for your dataset that you have read form a myFile.csv file
myData <- read.csv(file='myFile.csv', header=TRUE)
head(myData) # will show the first 5 entries in you imported data
# use whatever you need from the BBMM package now ....
Check RODBC package. You can find an example in R Data Import/Export. You can query data from excel sheet as if from a database table.
The benefit of reading Excel sheet with RODBC is that you get dates (if you work with any) in a proper format. With intermediate CSV, you'd need to specify a column type, unless you want it to be a factor or string. Also you can query only a portion of your data if you need so thus making subset() unnecessary.