Export an Analyze data table to PlaidCloud Document as a CSV delimited file.
See details here: Source and Target
The Export CSV transform is used to export data tables into delimited text files saved in PlaidCloud Document. This includes, but is not limited to, the following delimiter types:
To specify a custom delimiter, select User Defined Separator –> and then Other –>, and type the custom delimiter into the text box.
The Text Qualifier section allows users to specify how to handle data with quotation marks and escape characters. Choose from the following settings:
Lastly, the Use Windows Compatible Line Endings checkbox is selected by default to ensure compatibility with Windows systems. It is advisable to leave this setting on unless working in a unix-only environment.
All exported files are uncompressed, but the following compression options are available:
The Table Data Selection tab is used to map columns from the source data table to the target data table. All source columns on the left side of the window are automatically mapped to the target data table depicted on the right side of the window. Using the Inspect Source menu button, there are a few additional ways to map columns from source to target:
In addition to each of these options, each choice offers the ability to preview the source data.
If the source and target column options aren’t enough, other columns can be added into the target data table in several different ways:
Selecting Propagate All may effectively create a duplicate of every column. Analyze does not check to see if the columns are already mapped. Make sure duplicate column names do not exist.
To delete columns from the target data table, select the desired column(s), then right click and select Delete.
To rearrange columns in the target data table, select the desired column(s), then right click and select Move to Top, Move Up, Move Down, or Move to Bottom.
To return only distinct options, select the Distinct menu option. This will toggle a set of checkboxes for each column in the source. Simply check any box next to the corresponding column to return only distinct results.
When the target data table contains only a subset of the source data table, select the check box next to only the columns which are to be included in the target data table. Selecting all checkboxes could provide output that does not appear to be distinct.
To aggregate results, select the Summarize menu option. This will toggle a set of drop down boxes for each column in the target data table. The following summarization options are available:
For more aggregation details, see the Analyze overview page [here](/docs/analyze/#aggregation).
To allow for maximum flexibility, data filters are available on the source data and the target data. For larger data sets, it can be especially beneficial to filter out rows on the source so the remaining operations are performed on a smaller data set.
Any valid Python expression is acceptable to subset the data. Please see Expressions for more details and examples.
Compound filters must have individual elements wrapped in parentheses. For example, if filtering for Temperature and Humidity, a valid filter would look like this:
To report duplicates, select the Report Duplicates in Table checkbox and then specify an output table which will contain all of the duplicate records.
This will not remove the duplicate items from the target data table. To remove duplicate items, use the Distinct menu options as specified in the [Table Data Selection](../transforms/common_features#table-data-selection) section.
Example code here
See details here: Source Table Slicing
See details here: Select Subset of Final Data
See details here: Final Data Table Slicing
In this example, the Analyze target table, Import Google Spreadsheet, is exported to a text file named Export CSV comma delimited. As suggested by the name, the output file is comma delimited and will be given a .csv file extension. The target directory is the Analyze Demo Output directory of PlaidCloud Document. No compression is used.
All columns are mapped from source to target as Float, String, or Datetime data types, for number data, string data, and date data, respectively. No additional operations are performed.
In this example, the Analyze target table, Import Google Spreadsheet, is exported to a text file named Export CSV tab delimited and zipped. As suggested by the name, the output file is tab delimited and will be given a .tsv file extension. The target directory is the Analyze Demo Output directory of PlaidCloud Document. The Index column is used. Zip compression is used, so the file itself will be saved within a Zip file.
Only a subset of columns are mapped from source to target as Float, String, or Datetime data types, for number data, string data, and date data, respectively. No additional operations are performed.
Final Data Frame Slicing (Limit) is used to limit final output to 35 rows of data.