Note that FlowJo DOES NOT save your FCS files as part of the Workspace. Keywords associated with your data files.įor more on workspaces, please see our description of the FlowJo Workspace and reconnecting samples to a. all gates and statistic nodes that have been added to samples or groupsĪll compensation matrices, either acquisition defined or FlowJo defined. The workspace is the central hub for all activity in FlowJo, and saving as a workspace will save:Ī list of all the samples added to the WorkspaceĪ list of all the groups that have been createdĪll of the analyses, i.e. In such cases, we can specify the delimiter and line terminator as follows: csvreader = csv.Here’s some details from the flowJo website: Also, the rows are separated by two newlines instead of one. We notice that the delimiter is not a comma but a semi-colon.
Here, the file object ( csvfile) is converted to a DictWriter object. Writer = csv.DictWriter(csvfile, fieldnames = fields) of rows: %d"%(csvreader.line_num))Ĭsvreader.line_num is nothing but a counter which returns the number of rows which have been iterated. If you try to print each row, one can find that row is nothing but a list containing all the field values. Each row is appended to a list called rows.
Now, we iterate through remaining rows using a for loop. Since the first row of our csv file contains the headers (or field names), we save them in a list called fields. next() method returns the current row and advances the iterator to the next row. We save the csv.reader object as csvreader.Ĭsvreader is an iterable object. The file object is converted to csv.reader object. Here, we first open the CSV file in READ mode. Let us try to understand this piece of code. Run this program with the aapl.csv file in same directory. The above example uses a CSV file aapl.csv which can be downloaded from here. The output of above program looks like this: