csv2numbers 1.0.1

Automator scripts

Converter for CSV to Apple Numbers

csv2numbers is a command-line utility to convert CSV files to Apple Numbers spreadsheets.

Installation

The script is best installed using pip:

python3 -m pip install csv2numbers

You may need to install numbers-parser first including python-snappy according to the instructions at numbers-parser.

Usage

Use csv2numbers to print command-line usage. You must provide at least one CSV file on the command-line and can provide multiple files, which will then all be converted using the same parameters. Output files can optionally be provided, but is none are provided, the output is created by replacing the input's files suffix with .numbers. For example:

csv2numbers file1.csv file2.csv -o file1.numbers file2.numbers

CSV files are read using the Excel dialect.

The following options affecting the output of the entire file. The default for each is always false.

• --whitespace: strip whitespace from beginning and end of strings and collapse other whitespace into single space
• --reverse: reverse the order of the data rows
• --no-header: CSV file has no header row
• --day-first: dates are represented day first in the CSV file

csv2numbers can also perform column manipulation. Columns can be identified using their name if the CSV file has a header or using a column index. Columns are zero-indexed and names and indices can be used together on the same command-line. When multiple columns are required, you can specify them using comma-separated values. The format for these arguments, like for the CSV file itself, the Excel dialect.

Deleting columns

Delete columns using --delete. The names or indices of the columns to delete are specified as comma-separated values:

csv2numbers file1.csv --delete=Account,3

Renaming columns

Rename columns using --rename. The current column name and new column name are separated by a : and each renaming is specified as comma-separated values:

csv2numbers file1.csv --rename=2:Account,"Paid In":Amount

Date columns

The --date option identifies a comma-separated list of columns that should be parsed as dates. Use --day-first where the day and month is ambiguous anf the day comes first rather than the month.

Transforming columns

Columns can be merged and new columns created using simple functions. The --transform option takes a comma-seperated list of transformations of the form NEW:FUNC=OLD. Supported functions are:

• MERGE: the new column merges values from other columns with the chosen value being the first non-empty value
• NEG: the new column contains absolute values of any column that is negative; this is useful for isolating debits from account exports
• POS: the new column contains values of any column that is positive; this is useful for isolating credits from account exports

Examples:

csv2numbers --transform="Paid In"=POS:Amount,Withdrawn=NEG:Amount file1.csv

License

All code in this repository is licensed under the MIT License