1. Python Csv To Excel File
2. Csv To Excel Python
3. Convert Csv To Excel Python

Anvil apps have a full Python instance server-side, which makes it simple to import data from CSVs and Excel files into your Data Tables.

1. Convert Python Classes to Excel Spreadsheet. You already saw how to convert an Excel spreadsheet’s data into Python classes, but now let’s do the opposite. Let’s imagine you have a database and are using some Object-Relational Mapping (ORM) to map DB objects into Python classes. Now, you want to export those same objects into a spreadsheet.
2. Contribute to wxwwt/opencv-picture-to-excel development by creating an account on GitHub.

20 minutes ago  A strange one really.Trying to load a csv onto an IBMi, just a standard csv file, when I use python pandas.tocsv, the file won't load, but if I import the same file into excel (using import), then save as.csv (used the UTF-8, csv and MSDOS csv - all work); the file loads; which suggests the df.tocsv is different to the standard excel.csv. Hi @Lina, you can use this: numpyarray = np.genfromtxt('file.csv', delimiter=';', skipheader=1) the arguments inside the brackets are the file name, the delimiter, and skipheader set to 1 will make the csv load to an array without the header row.

There are two ways to do this:

1. Using a FileLoader Component in a running Anvil app
2. Accessing files locally using the Anvil Uplink

We’ll cover both methods, and you can download our sample CSV and Excel files here:

File upload in a running app

First, we’ll import data to Anvil’s Data Tables using a FileLoader component in a running Anvil app.

Create a new app, add the Data Tables service, and create a table.

Ensure that ‘Auto-create missing columns when adding rows’ in the top right hand corner is checked:

Add a Server Module, and select the ‘Full Python 3’ runtime in the dropdown in top right:

Add these lines to your Server Module:

Go back to ‘Form1’, and drop a FileLoader component into your UI.

The FileLoader’s change event is raised when a user selects a file. Its file argument is a Media object containing the chosen file.

Double click the FileLoader in your UI to create the file_loader_1_change event, and edit the function to look like this:

Run your app, and upload a CSV or excel file into the FileLoader component.

Stop your app, navigate to your Data Tables, and you’ll see your data has been imported.

Uplink script

If you’d rather access your files locally with Python, rather than uploading them in a running Anvil app, you can use the Uplink to do this.

Python Csv To Excel File

Create a new app, add the Data Tables service, and create a table.

Ensure that ‘Auto-create missing columns when adding rows’ in the top right hand corner is checked:

We’ll use the pandas and xlrd libraries, so install these:

Import from CSV

This Python script will import data from a CSV file to your Data Table:

Import from Excel

This Python script will import data from an Excel file to your Data Table:

Next, install the Anvil Uplink library:

Csv To Excel Python

Enable the Uplink in your app, and then paste the connection code into your script:

Run your scripts

Run your script, calling your functions and passing in the CSV or Excel files you want to import.

Stop your app, navigate to your Data Tables, and you’ll see your data has been imported.

Example script

Here’s an example script that uploads both colours.csv and colours.xlsx to an Anvil Data Table:

Convert Csv To Excel Python