econicer 0.23

A small program to analyse financial transactions

econicer

This tool enables the analysis of transaction data of a bank account.

The transaction data is analysed for specific keywords and grouped into custom categories. The grouping information is used to created plots and an automated report.

Installation

Install econcier with pip (not working yet)

Requirements

At first your bank must provide a function to download all your transaction as a CSV file, otherwise econcier would be of much use. The CSV file should have some header information and a table of your transactions with specific fields, see Section Config Files.

All requirements for Python are found in the 'requirements.txt' file and should be installed already if you used PyPi.

Furthermore, a Latex installation is needed for the creation of automated reports. Econicer uses the 'xelatex' compiler. An installation of Miktex should be sufficient.

Config Files

Econcier needs 2 separate configuration files for account management.

• bank.json - describes the structure of the CSV file from your bank
• grouping.json - defines you indented grouping of transactions by specific data fields

First, the 'bank.json' file contains information of how the file from your bank is structured. Econicer expects a certain information and you have to specify where this information can be found in your file.

The other file 'grouping.json' specifies all groups, keywords and fields, which are searched by econicer. Single groups are specified by a key, which is follow by a list of keywords. Econicer uses those keywords to assign a group to every single transactions. The groups are prioritized, such as the first groups is preferred over the second. The grouping algorithm will only look into fields, which are set in the "dbIdentifier" list.

Tutorial

The example folder holds all files for the tutorial, but first make sure you install econicer with pip. The config files are included in the tutorial folder. Download the tutorial files from the git repo folder 'tutorial'. Copy all contents from 'tutorial' to a directory, where you want econicer to work.

First, the account has to be initialized by running

py -m econicer -i Tutorial

This will create the '.db' folder, where eocnicer stores all information.

If you have multiple accounts in the database. After initializing, you can switch them with

py -m econicer -c OtherAccountName

For quick look at your current settings run

py -m econicer -ls

Adding Transaction Files

After the initialization you can start with adding transaction data to the account. Make sure, that you are on the correct account before adding the data from your bank.

A example file can be added by

py -m econicer -a files\firstFile.csv

Econicer reads the file data and merges the current database content with the file. Add a second file by

py -m econicer -a files\secondFile.csv

There is the option of undoing the last action with

py -m econicer -u

but this only works for one step back yet.

Grouping Transactions

A key feature of econicer is to group your transactions. When you add some data to your account, econicer will apply the groups defined in the group settings file. The grouping is used in the later analysis.

The grouping depends on the keyword lists specified in the 'grouping.json' file. Let's check if all transactions got grouped by

py -m econicer -n

In this example no all transactions have a groups. You need to be familiar with editing json files. Let's fix this by add a the keywords 'electricity' and 'supplies' the to 'lining' group in the 'grouping.json' file. Additionally, lets a new group. The new group can be called 'hobby' with the keyword 'guitar' to show how much money we spend on our lining hobbies.

Run the regroup command to apply the new grouping settings.

py -m econicer -g

Now all transactions should have a group assigned.

Further Analyzing your Transaction History

To analyse the database by searching for a word in the fields. The default field is the 'usage' field. Fields can be specified as list with the -k flag. Use

py -m econicer -s store -k customer usage

to search for the word "store" in the fields 'customer' and 'usage'.

Automated Report and Plots

Finally, Create an automated report with Latex by

py -m econicer -r

You also can create only the plots for the report, if you don't have Latex.

py -m econicer -p