DataSorter

DataSorter is a simple tool for quickly sorting large amounts of data into categories. It scans a data table row by row and, based on a set of filters, assigns a tag to each row. If no filter matches a given row, it lets the user add a new filter with a few simple clicks.

Dependencies

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DataSorter requires python 3.7 or newer as well as the following python packages:

• click
• pandas
• tkinter

Usage

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Usage: data_sorter.py [OPTIONS]

  Sort data into categories.

Options:
  -e, --encoding TEXT      CSV encoding  [default: windows_1258]        
  -s, --separator TEXT     CSV separator  [default: ,]
  -i, --input-file TEXT    Input CSV file  [default: data/data.csv]     
  -o, --output-file TEXT   Output CSV file  [default: data/data_out.csv]
  -f, --filters-file TEXT  CSV file containing the filters  [default:   
                           data/filters.csv]
  -h, --help               Show this message and exit.

Example

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Say you have a list of wire transfers from and into your bank account, and you want to get an overview of how you are spending your money each month. For this, you want to group the long list of wire transfers into a small number of categories, such as Cost of Living or Rent. Instead of going through the list and tagging each entry manually, you can use DataSorter to add categories automatically.

Let's say this is the list of wire transfers:

Date	Recipient	Purpose	Amount (USD)
19/11/20	Superstore	Thank you for shopping at Superstore!	83.62
18/11/20	Torgot	Thank you for shopping at Torgot!	72.48
15/11/20	PayPal	Your monthly Netflix subscription	9.99
7/11/20	Torgot	Thank you for shopping at Torgot!	143.35
01/11/20	John Doe	Monthly Rent	941.5

You can then define a list of filters that search for a match in the Recipient or the Purpose field and assigns the respective category.

Recipient	Purpose	Category
Superstore		Cost of Living
	Netflix	Recreation
	Rent	Rent

Note that there is no matching filter for the second wire transfer. If this happens, DataSorter prompts you to add a new filter. It populates the text input boxes with the according cells from the data table for you to modify before adding a new filter:

Clicking Add Filter will then add a new filter to the list which will be written to the respective CSV file at the end.

This makes sifting through large amounts of data, adding new filters where needed, fast and simple.

This is the result of running DataSorter on the example input:

Date	Recipient	Purpose	Amount (USD)	Category
19/11/20	Superstore	Thank you for shopping at Superstore!	83.62	Cost of Living
18/11/20	Torgot	Thank you for shopping at Torgot!	72.48	Cost of Living
15/11/20	PayPal	Your monthly Netflix subscription	9.99	Recreation
7/11/20	Torgot	Thank you for shopping at Torgot!	143.35	Cost of Living
01/11/20	John Doe	Monthly Rent	941.5	Rent