Python Pandas - 写入 to_csv 时使用多字符分隔符

Question

It appears that the pandas to_csv function only allows single character delimiters/separators.

Is there some way to allow for a string of characters to be used like, "::" or "%%" instead?

I tried:

df.to_csv(local_file,  sep = '::', header=None, index=False)

and getting:

TypeError: "delimiter" must be a 1-character string

Answer 1

Use numpy-savetxt

Ex:

np.savetxt(file.csv, np.char.decode(chunk_data.values.astype(np.bytes_), 'UTF-8'), delimiter='~|', fmt='%s',encoding=None)

np.savetxt(file.dat, chunk_data.values, delimiter='~|', fmt='%s',encoding='utf-8')

Answer 2

Think about what this line a::b::c' means to a standard CSV tool: an a , an empty column, a b , an empty column, and a c . Even in a more complicated case with quoting or escaping: "abc::def"::2 means an abc::def , an empty column, and a 2.

So, all you have to do is add an empty column between every column, and then use : as a delimiter, and the output will be almost what you want.

I say “almost” because Pandas is going to quote or escape single colons. Depending on the dialect options you're using, and the tool you're trying to interact with, this may or may not be a problem. Unnecessary quoting usually isn't a problem (unless you ask for QUOTE_ALL , because then your columns will be separated by :"": , so hopefully you don't need that dialect option), but unnecessary escapes might be (eg, you might end up with every single : in a string turned into a \\: or something). So you have to be careful with the options. But it'll work for the basic “quote as needed, with mostly standard other options” settings.