Importing and exporting data from a dataset
The CSV import feature in your dataset will help you transfer data from a CSV file or a spreadsheet with a .csv extension to your Kissflow dataset. Once imported, your CSV rows will appear as rows in your dataset, and each column will contain metadata about your data.
Organizing the data in your CSV file
The CSV Import feature allows you to import data in bulk into Kissflow. Here are some guidelines to follow when preparing a CSV file for import:
- Mandatory fields: If mandatory fields exist in your Dataset form, you must map at least one column in your CSV file with the required fields.
- Data: Within the CSV file, you can map only the following field types to your dataset: Text, Text area, Number, Rating, Date, Date-time, Currency, Yes/no, User, Single-select dropdown, Multi-select dropdown, Slider, and Checkbox.
- You cannot import data from a CSV file for the following field types: Attachment, checklist, signature, and image.
- For Yes/No fields, you can use any binary values: True/False, 1/0, Yes/No.
- Delimiter: You must only use the comma (,) as a delimiter inside the CSV file.
- Rows: The CSV file can have up to 50,000 rows, excluding the header.
Note
Though the default dataset row limit is 50,000, it can be increased at no cost upon request. Please contact the support team for a limit increase.
- Columns: Your CSV file can have up to 100 columns. This limit cannot be increased. The CSV column names can be alphanumeric but should contain only the following characters: space, hyphen (-), and underscore (_).
- Encoding: The CSV file must have a .csv extension that supports UTF-8 encoding.
Supported date and time format
- The supported date formats
Data Format |
Example |
DD-MMM-YY |
02-DEC-20 |
DD-MMM-YYYY |
02-DEC-2020 |
DD/MM/YY |
02/12/20 |
DD/MM/YYYY |
02/12/2020 |
MM/DD/YY |
12/02/20 |
MM/DD/YYYY |
12/01/2020 |
DD.MM.YY |
02.12.20 |
DD.MM.YYYY |
02.12.2020 |
DD-MM-YYYY |
02-12-2020 |
YYYY-MM-DD |
2020-12-02 |
The supported datetime formats
Datetime Format |
Example |
DD-MMM-YYTHH:mmZ |
01-Jan-20T12:00Z |
DD-MMM-YY hh:mm A |
01-Jan-20 05:00 AM |
DD-MMM-YY HH:mm |
01-Jan-20 05:00 |
DD-MMM-YYYY HH:mm |
01-Jan-2020 05:00 |
DD-MMM-YYYY hh:mm A |
01-Jan-2020 05:00 AM |
DD-MMM-YYYYTHH:mmZ |
01-Jan-2020T05:00Z |
DD/MM/YY HH:mm |
01/12/20 05:00 |
DD/MM/YYTHH:mmZ |
01/12/20T12:00Z |
DD/MM/YY hh:mm A |
01/12/20 12:00 AM |
MM/DD/YY HH:mm |
12/01/20 12:00 |
MM/DD/YYTHH:mm |
12/01/20T12:00 |
MM/DD/YY hh:mm A |
12/01/20 12:00 AM |
MM/DD/YYYY HH:mm |
12/01/2020 12:00 |
MM/DD/YYYYTHH:mmZ |
12/01/2020T12:00Z |
MM/DD/YYYY hh:mm A |
12/01/2020 12:00 AM |
DD.MM.YY HH:mm |
01.12.20 12:00 |
DD.MM.YYTHH:mmZ |
01.12.20T12:00Z |
DD.MM.YY hh:mm A |
01.12.20 12:00 PM |
DD.MM.YYYY HH:mm |
01.12.2020 12:00 |
DD.MM.YYYYTHH:mmZ |
01.12.2020T12:00+05:30 |
DD.MM.YYYY hh:mm A |
01.12.2020 12:00 PM |
- Timestamp formats
Timestamp |
Example |
D - Date |
DD - 01, 24 |
M - Month |
MM - 01, 02, 12 MMM - Jan, Feb |
Y - Year |
YY - 99, 00, 01 YYYY - 1999, 2001 |
T - Constant Character (As per ISO) |
T |
H - 24 Hour |
HH - 05, 17 |
h - 12 Hour |
hh - 03, 05 |
m - Minute |
mm - 00, 15, 59 |
A - Meridiem |
A - AM, PM |
Z - Time Zon |
Z - Z, +05:30 |
Once you have confirmed that your CSV file meets the above requirements, follow these steps to import the CSV data to your Kissflow Dataset:
- Sign in to your Kissflow account. If you haven't already, create a new dataset.
- On the top right section of the page, click Import CSV beside the Share button.
- After the file picker opens, click Choose your files, browse your documents, and select your desired file with a .csv extension.
- After importing the CSV file, the system checks it for file corruption and delimiter errors. If you find an issue, please correct it in the CSV file before re-uploading it.
- Click Next to continue. Then choose the columns from your CSV file that you would like to appear in the dataset. You must map the columns in your CSV file to the fields in your dataset. For example, you can choose to map the email addresses from your CSV document into the Email field in your dataset.
Note:
CSV header names and data fields must be of the same data type.
After mapping the dataset values, you will have the choice to handle the data in your dataset:
- You can either add new rows and update existing rows, or add only new rows while importing the data.
- You can delete or keep the dataset rows that are not in the CSV file.
- You can skip specific rows or cancel the import in case of errors.
After you have selected your options, click Next. Your data will begin importing.
You can close the window and continue working while waiting for all your data to be imported into your dataset. After the import is complete, you will be notified via email and push notifications.
There are 3 possible scenarios.
All the imported data was successfully uploaded into the dataset.
Some of the data was imported successfully, but some rows failed. You can download the failed rows, work on them, and upload the file again.
The import was aborted. View the error logs to see what went wrong.
Exporting data from a dataset
To export a data from a dataset, follow these steps:
- Click the Export button on the top right side of the screen next to the Filter button.
- You can export data in two file types: CSV file and TXT file.
- Choose the file you prefer and click Export.
- After exporting, you will receive an email link to the exported file.
FAQ
Q) Can I use the Import CSV option in the dataset when auto-lookup is enabled in your dataset's lookup field?
Ans) When an auto lookup is enabled, you cannot use the import CSV option for a lookup column in Dataset. Auto lookup is designed to automatically populate the lookup column based on existing data relationships, which conflicts with manually importing data for that column.