This information is used to convert the decoded data to our website's character set so that all letters and symbols can be displayed properly. It is usually UTF-8, but can be many others if you are not sure then play with the available options or try the auto-detect option. Character set: In case of textual data, the encoding scheme does not contain the character set, so you have to specify which character set was used during the encoding process.Base64 is used commonly in a number of applications including email via MIME, as well as storing complex data in XML or JSON. This encoding helps to ensure that the data remains intact without modification during transport.
Base64 encode your data without hassles or decode it into a human-readable format.īase64 encoding schemes are commonly used when there is a need to encode binary data, especially when that data needs to be stored and transferred over media that are designed to deal with text. So maybe this is confusing chardet and charset_normalizer, as I think they work best on normal language.Meet Base64 Decode and Encode, a simple online tool that does exactly what it says: decodes from Base64 encoding as well as encodes into it quickly and easily. Keep in mind that I'm expecting the files to have this format: datetime,ask,bid,vol I've also tried to manually run code(enc, 'ignore') for all encodings supported in Python, and I manually checked if any of the results weren't absolute gibberish, but that also didn't work. This is what I get: tried using chardet and charset_normalizer but they both failed to recognize any encoding. If I try this for the first three files I'm trying to decode: with open(data_file, "rb") as f: The only way I can get Pandas to read this files without raising exceptions is this: for chunk in pd.read_csv(data_file, index_col=False, sep=r'\s\s+', chunksize=10**3, engine="python"): dat files into Pandas but I don't know the encoding of the binary data.
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