Rename columns¶

The rename_columns operations uses a dictionary to map old column names into new ones.

Purpose¶

Use this operation to:

Standardize column names across datasets
Make column names more descriptive or meaningful
Correct column naming errors
Conform to naming conventions (e.g., BIDS standards)

Parameters¶

Parameters for rename_columns.

Parameter	Type	Description
column_mapping	dict	The keys are the old column names and the values are the new names.
ignore_missing	bool	If false, a `KeyError` is raised if a dictionary key is not a column name.

If ignore_missing is false, a KeyError is raised if a column specified in the mapping does not correspond to a column name in the data file.

Example¶

The following example renames the stop_signal_delay column to be stop_delay and the response_hand to be hand_used.

A JSON file with a single rename_columns transformation operation.

[{   
    "operation": "rename_columns",
    "description": "Rename columns to be more descriptive.",
    "parameters": {
        "column_mapping": {
            "stop_signal_delay": "stop_delay",
            "response_hand": "hand_used"
        },
        "ignore_missing": true
    }
}]

Results¶

The results of executing the previous rename_columns operation on the sample remodel event file are:

After the rename_columns operation is executed, the sample events file is:

onset	duration	trial_type	stop_delay	response_time	response_accuracy	hand_used	sex
0.0776	0.5083	go	n/a	0.565	correct	right	female
5.5774	0.5083	unsuccesful_stop	0.2	0.49	correct	right	female
9.5856	0.5084	go	n/a	0.45	correct	right	female
13.5939	0.5083	succesful_stop	0.2	n/a	n/a	n/a	female
17.1021	0.5083	unsuccesful_stop	0.25	0.633	correct	left	male
21.6103	0.5083	go	n/a	0.443	correct	left	male

Notes¶

Only renames columns; does not change data values
Multiple columns can be renamed in a single operation
Set ignore_missing to true for flexible operation across varied datasets
Column position in the file is not changed
Use the mapping dictionary to rename as many columns as needed
Common use: standardizing column names after importing from different sources