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This free online tool allows you to convert CSV format to TSV format.
CSV (Comma Separated Values) and TSV (Tab Separated Values) are two popular file formats for storing and exchanging data in a tabular format. While CSV uses commas to separate values in each row, TSV uses tabs to separate them. Sometimes, it may be necessary to convert CSV files to TSV format, especially when working with tools that require TSV input.
A CSV to TSV converter is a free online tool that can convert data stored in CSV format to TSV format. The converter reads a CSV file and creates a new TSV file with the same data but with tabs instead of commas as the separator.
CSV (Comma Separated Values) uses commas to separate values in each row, whereas TSV (Tab Separated Values) uses tabs. TSV files are often easier to read and edit than CSV files, especially when dealing with large amounts of data.
When you convert CSV data to TSV format, you can use certain tools and applications that require TSV input. Also, TSV files are often easier to read and edit than CSV files when dealing with large amounts of data.
Yes, many CSV to TSV converters also offers a reverse conversion option that allows you to convert TSV data back to CSV format. However, as with any data conversion, there may be some loss of information or formatting during the conversion process.
The size limit of the CSV file that can be converted to TSV format varies depending on the specific CSV to TSV converter being used. However, many converters can handle large CSV files without consuming too much memory or CPU.
If you need to convert files inside a script or data pipeline instead of pasting them in by hand, both Python and DuckDB can turn CSV into TSV in a single command. The only real change is swapping the comma delimiter for a tab, so your columns line up on tab stops instead of commas.
The pandas library reads a CSV into a DataFrame and writes it back out with a tab separator. Passing index=False stops pandas from adding an extra row-number column to the output.
import pandas as pd
# Read the CSV, then write it back out as tab-separated
df = pd.read_csv("input.csv")
df.to_csv("output.tsv", sep="\t", index=False)If you would rather avoid a dependency, the standard-library csv module handles it too. It reads the comma-delimited rows and re-writes them with a tab delimiter, correctly preserving any quoted fields.
import csv
with open("input.csv", newline="") as f_in, \
open("output.tsv", "w", newline="") as f_out:
reader = csv.reader(f_in) # default comma delimiter
writer = csv.writer(f_out, delimiter="\t")
for row in reader:
writer.writerow(row)DuckDB can read and re-export a file in one SQL statement, which is handy for very large datasets. The COPY command below reads the CSV, keeps the HEADER row, and writes tab-separated output.
COPY (SELECT * FROM read_csv_auto('input.csv'))
TO 'output.tsv' (DELIMITER '\t', HEADER);A safe CSV to TSV conversion is more than a find-and-replace of commas with tabs. Well-formed CSV follows the RFC 4180 standard, which lets a single field contain commas, double quotes, or even line breaks as long as that field is wrapped in double quotes. The converter parses those rules first, so your data structure stays intact.
Converting a file with this tool takes only a few seconds - no installs and no sign-up required:
Two questions come up whenever data moves between formats: does the header survive, and will special characters stay intact? Here is how this converter handles both.
Yes. The converter parses your CSV according to the RFC 4180 standard, so a quoted field like "Doe, John" stays one value and escaped double quotes ("") are restored to a single quote. Commas inside quoted fields are kept as text rather than being mistaken for column breaks.
Yes. The first row is converted the same way as every other row - only the delimiter changes from a comma to a tab - so your column names appear as the header of the resulting TSV, in the same order.
The output is UTF-8. That means special characters - accented letters, currency symbols, emoji, and non-English text such as CJK characters - are preserved exactly, without being corrupted into question marks or mojibake.
The quickest way is pandas: read the file with pd.read_csv("input.csv") and write it back with df.to_csv("output.tsv", sep="\t", index=False). If you prefer no dependencies, the built-in csv module can read the rows and re-write them with csv.writer(..., delimiter="\t").
Yes. Because the conversion only swaps the delimiter and keeps every value, it is fully reversible. Use the TSV to CSV Converter to turn a tab-separated file back into comma-separated values.
Both Excel and Google Sheets open CSV and TSV files. TSV can be more reliable when your data itself contains commas, since a tab delimiter removes any ambiguity about where a column ends - which is a common reason to convert CSV to TSV before importing.
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