diff --git a/anonymize_table.py b/anonymize_table.py
new file mode 100755
index 0000000..720de11
--- /dev/null
+++ b/anonymize_table.py
@@ -0,0 +1,151 @@
+#!/usr/bin/env python3
+
+import re
+import random
+import string
+import logging
+import numpy as np
+from pathlib import Path
+
+import ontoweaver
+
+def write_table(df, fd, ext="csv", **kwargs):
+
+    read_funcs = {
+        'csv'    : df.to_csv,
+        'tsv'    : df.to_csv,
+        'txt'    : df.to_csv,
+
+        'xls'    : df.to_excel,
+        'xlsx'   : df.to_excel,
+        'xlsm'   : df.to_excel,
+        'xlsb'   : df.to_excel,
+        'odf'    : df.to_excel,
+        'ods'    : df.to_excel,
+        'odt'    : df.to_excel,
+
+        'json'   : df.to_json,
+        'html'   : df.to_html,
+        'xml'    : df.to_xml,
+        'hdf'    : df.to_hdf,
+        'feather': df.to_feather,
+        'parquet': df.to_parquet,
+        'pickle' : df.to_pickle,
+        'orc'    : df.to_orc,
+        'stata'  : df.to_stata,
+    }
+
+    if ext not in read_funcs:
+        msg = f"File format '{ext}' of file '{filename}' is not supported (I can only write one of: {' ,'.join(read_funcs.keys())})"
+        logger.error(msg)
+        raise RuntimeError(msg)
+
+    return read_funcs[ext](path_or_buf=fd, **kwargs)
+
+
+def shuffle(df):
+    # df.apply(np.random.shuffle, axis = 0) # columns
+    return df.apply(lambda col: col.sample(frac=1).values)
+
+
+def anonymize_value(value, remove_site = False):
+    assert(";" not in str(value))
+    if remove_site:
+        value = re.sub("_DNA[1-2]*$", "", value)
+    m = re.search("^([A-Z]{1,2}[0-9]{3})", value)
+    if m:
+        code = m.group(1)
+        return re.sub(code, random_code(), value)
+    else:
+        return value
+
+
+def anonymize_all(df, columns=None, remove_site = False):
+    if not columns:
+        columns = df.columns.values.tolist()
+    for i,row in df.iterrows():
+        for col in columns:
+            value = row[col]
+            if type(value) == str:
+                if ";" in value:
+                    vals = []
+                    for val in value.split(";"):
+                        new = anonymize_value(val, remove_site)
+                        vals.append(new)
+                    new_val = ";".join(vals)
+                else:
+                    new_val = anonymize_value(value, remove_site)
+
+                if value and new_val:
+                    df.loc[i,col] = new_val
+
+
+def random_code():
+    return "CC" + "".join(random.choices(string.digits, k=4))
+
+
+if __name__ == "__main__":
+    import argparse
+    import os
+    import sys
+
+    do = argparse.ArgumentParser(
+        formatter_class=argparse.RawTextHelpFormatter,
+        description="""Anonymize or pseudonymize a data table.""",
+        epilog=f"Example:\n\t./{os.path.basename(sys.argv[0])} data.csv --args index:False --remove-sample-site --format csv > data_anon.csv")
+
+    do.add_argument("--log-level",
+        default="INFO",
+        choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'],
+        help="Configure the log level (default: %(default)s).",
+    )
+
+    do.add_argument('-c', '--columns', nargs='+', default=None,
+        help="Columns names in which to anonymize cohort codes (default: all).")
+
+    do.add_argument('-s', '--remove-sample-site', action="store_true")
+
+    do.add_argument('-S', '--no-shuffle', action="store_true")
+
+    # do.add_argument('-c', '--eoc', help="Use the given (;-separated) mapping instead of generating a random one.", metavar="EOC_FILE")
+
+    do.add_argument('-f', '--format', help="File format to export the altered data (default: same as input).", default=None, metavar="FMT")
+
+    do.add_argument('-a', '--args', help="Additional argument to pass to the pandas.DataFrame.to_* write function (default: none).", default=None, nargs='+', metavar="KEY:VAL")
+
+
+    do.add_argument("filename", metavar="DATABASE_FILE")
+
+    asked = do.parse_args()
+
+    logging.basicConfig(level = asked.log_level)
+
+    if not asked.format:
+        asked.format = Path(asked.filename).suffix[1:]
+
+    more_args = {}
+    if asked.args:
+        for kv in asked.args:
+            k,v = kv.split(":")
+
+            if v == "False":
+                v = False
+            elif v == "True":
+                v = True
+
+            more_args[k] = v
+
+    logging.info("Load file...")
+    df = ontoweaver.read_file(asked.filename)
+    print(df, file=sys.stderr)
+
+    if not asked.no_shuffle:
+        logging.info("Shuffle columns...")
+        df = shuffle(df)
+
+    logging.info("Alter cohort codes...")
+    anonymize_all(df, columns = asked.columns, remove_site = asked.remove_sample_site)
+
+    logging.info("Write data...")
+    write_table(df, sys.stdout, ext=asked.format, **more_args)
+