CLEVERCSV-STANDARDIZE(1)

💖 CLEVERCSV-STANDARDIZE(1) 💖

okay bestie, welcome to the Clevercsv Manual ✨ this is the glow-up page for clevercsv-standardize, and yes it's giving main character energy. settle in, we're making your cursed lil CSV files look presentable.

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🌸 NAME 🌸

clevercsv-standardize — Convert a CSV file to one that conforms to RFC-4180 💅

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🦋 SYNOPSIS 🦋

clevercsv standardize [-e ENCODING | --encoding=ENCODING]
                      [-E TARGET_ENCODING | --target-encoding=TARGET_ENCODING]
                      [-i | --in-place] [-n NUM_CHARS | --num-chars=NUM_CHARS]
                      [-o OUTPUT | --output=OUTPUT] [-t | --transpose]
                      <path [path ...]>

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🎀 DESCRIPTION 🎀

so the standardize command is literally here to take your non-standard CSV file and convert it into the standard RFC-4180 format [1]. no cap, it's the makeover montage your data deserves 💖

when you use the --in-place option, you can use the return code of CleverCSV to check whether a file was altered or not. the return code will be 2 when the file was altered and 0 otherwise. (yes, 2, not 1. we're quirky like that ✨)

[1]: https://tools.ietf.org/html/rfc4180

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✨ OPTIONS ✨

• -h, --help — show this help message and exit 🫶
• -e, --encoding — the file encoding of the given CSV file is automatically detected using chardet. and like, chardet is incredibly accurate, but it's not perfect, bestie 😭 so in the rare cases that it makes a mistake in detecting the file encoding, you can override the encoding by providing it through this flag. for this command, the provided encoding will also be used for the output file(s). when only one encoding is given, it will be used for all files given on the command line. when multiple encodings are given, the number must correspond to the number of files provided as input. (match the counts or it's not gonna go how you want 🚨)
• -E, --target-encoding — if omited, the output file encoding while be the same as that of the original file. (that's the original's energy, unchanged, no notes 💜)
• -i, --in-place — Standardize and overwrite the input file(s) 🔥 bold. brave. iconically risky.
• -n, --num-chars — on large CSV files, dialect detection can sometimes be a bit slow due to the large number of possible dialects to consider. to alleviate this, you can limit the number of characters to use for detection.

one aspect to keep in mind is that CleverCSV may need to read a specific number of characters to be able to correctly infer the dialect. for example, in the imdb.csv file in the GitHub repository, the correct dialect can only be found after at least 66 lines of the file are read. therefore, if there is availability to run CleverCSV on the entire file, that is generally recommended. 👑

• -o, --output — the output files to write the standardized input files to. the order of the input files and the order of the output files should match if this option is used with more than one input file. keep the vibes aligned, fr fr 🦋
• -t, --transpose — transpose the columns of the input file(s) before writing 🌀 (chaotic, but make it fashion)
• <path> — Path to one or more CSV file(s) 🍓

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💅 CLEVERCSV 💅

part of the CleverCSV suite 🌈

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and that's the whole page, bestie! you slayed 💖 no cap, this was clevercsv 0.8.5, dated 2026-05-11, from the Clevercsv Manual. now go standardize something, you icon 👑✨🎀