xorbits.pandas.DataFrame.to_csv#

DataFrame.to_csv(path, sep=',', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, mode='w', encoding=None, compression='infer', quoting=None, quotechar='"', lineterminator=None, chunksize=None, date_format=None, doublequote=True, escapechar=None, decimal='.', storage_options=None)#

Write object to a comma-separated values (csv) file.

参数

  • path_or_buf (str, path object, file-like object, or None, default None (Not supported yet)) –

    String, path object (implementing os.PathLike[str]), or file-like object implementing a write() function. If None, the result is returned as a string. If a non-binary file object is passed, it should be opened with newline=’’, disabling universal newlines. If a binary file object is passed, mode might need to contain a ‘b’.

    在 1.2.0(pandas) 版更改: Support for binary file objects was introduced.

  • sep (str, default ',') – String of length 1. Field delimiter for the output file.

  • na_rep (str, default '') – Missing data representation.

  • float_format (str, Callable, default None) – Format string for floating point numbers. If a Callable is given, it takes precedence over other numeric formatting parameters, like decimal.

  • columns (sequence, optional) – Columns to write.

  • header (bool or list of str, default True) – Write out the column names. If a list of strings is given it is assumed to be aliases for the column names.

  • index (bool, default True) – Write row names (index).

  • index_label (str or sequence, or False, default None) – Column label for index column(s) if desired. If None is given, and header and index are True, then the index names are used. A sequence should be given if the object uses MultiIndex. If False do not print fields for index names. Use index_label=False for easier importing in R.

  • mode ({'w', 'x', 'a'}, default 'w') –

    Forwarded to either open(mode=) or fsspec.open(mode=) to control the file opening. Typical values include:

    • ’w’, truncate the file first.

    • ’x’, exclusive creation, failing if the file already exists.

    • ’a’, append to the end of file if it exists.

  • encoding (str, optional) – A string representing the encoding to use in the output file, defaults to ‘utf-8’. encoding is not supported if path_or_buf is a non-binary file object.

  • compression (str or dict, default 'infer') –

    For on-the-fly compression of the output data. If ‘infer’ and ‘path_or_buf’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, ‘.xz’, ‘.zst’, ‘.tar’, ‘.tar.gz’, ‘.tar.xz’ or ‘.tar.bz2’ (otherwise no compression). Set to None for no compression. Can also be a dict with key 'method' set to one of {'zip', 'gzip', 'bz2', 'zstd', 'xz', 'tar'} and other key-value pairs are forwarded to zipfile.ZipFile, gzip.GzipFile, bz2.BZ2File, zstandard.ZstdCompressor, lzma.LZMAFile or tarfile.TarFile, respectively. As an example, the following could be passed for faster compression and to create a reproducible gzip archive: compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}.

    1.5.0(pandas) 新版功能: Added support for .tar files.

    May be a dict with key ‘method’ as compression mode and other entries as additional compression options if compression mode is ‘zip’.

    Passing compression options as keys in dict is supported for compression modes ‘gzip’, ‘bz2’, ‘zstd’, and ‘zip’.

    在 1.2.0(pandas) 版更改: Compression is supported for binary file objects.

    在 1.2.0(pandas) 版更改: Previous versions forwarded dict entries for ‘gzip’ to gzip.open instead of gzip.GzipFile which prevented setting mtime.

  • quoting (optional constant from csv module) – Defaults to csv.QUOTE_MINIMAL. If you have set a float_format then floats are converted to strings and thus csv.QUOTE_NONNUMERIC will treat them as non-numeric.

  • quotechar (str, default '"') – String of length 1. Character used to quote fields.

  • lineterminator (str, optional) –

    The newline character or character sequence to use in the output file. Defaults to os.linesep, which depends on the OS in which this method is called (’\n’ for linux, ‘\r\n’ for Windows, i.e.).

    在 1.5.0(pandas) 版更改: Previously was line_terminator, changed for consistency with read_csv and the standard library ‘csv’ module.

  • chunksize (int or None) – Rows to write at a time.

  • date_format (str, default None) – Format string for datetime objects.

  • doublequote (bool, default True) – Control quoting of quotechar inside a field.

  • escapechar (str, default None) – String of length 1. Character used to escape sep and quotechar when appropriate.

  • decimal (str, default '.') – Character recognized as decimal separator. E.g. use ‘,’ for European data.

  • errors (str, default 'strict' (Not supported yet)) – Specifies how encoding and decoding errors are to be handled. See the errors argument for open() for a full list of options.

  • storage_options (dict, optional) –

    Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to urllib.request.Request as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded to fsspec.open. Please see fsspec and urllib for more details, and for more examples on storage options refer here.

    1.2.0(pandas) 新版功能.

返回

If path_or_buf is None, returns the resulting csv format as a string. Otherwise returns None.

返回类型

None or str

参见

read_csv

Load a CSV file into a DataFrame.

to_excel

Write DataFrame to an Excel file.

实际案例

>>> df = pd.DataFrame({'name': ['Raphael', 'Donatello'],  
...                    'mask': ['red', 'purple'],
...                    'weapon': ['sai', 'bo staff']})
>>> df.to_csv(index=False)  
'name,mask,weapon\nRaphael,red,sai\nDonatello,purple,bo staff\n'

Create ‘out.zip’ containing ‘out.csv’

>>> compression_opts = dict(method='zip',  
...                         archive_name='out.csv')  
>>> df.to_csv('out.zip', index=False,  
...           compression=compression_opts)

To write a csv file to a new folder or nested folder you will first need to create it using either Pathlib or os:

>>> from pathlib import Path  
>>> filepath = Path('folder/subfolder/out.csv')  
>>> filepath.parent.mkdir(parents=True, exist_ok=True)  
>>> df.to_csv(filepath)  

>>> import os  
>>> os.makedirs('folder/subfolder', exist_ok=True)  
>>> df.to_csv('folder/subfolder/out.csv')  
Extra Parameters
----------------
path : str
    File path.
    If path is a string with wildcard e.g. '/to/path/out-*.csv',
    to_csv will try to write multiple files, for instance,
    chunk (0, 0) will write data into '/to/path/out-0.csv'.
    If path is a string without wildcard,
    all data will be written into a single file.

This docstring was copied from pandas.core.frame.DataFrame.