simpletable.dataframe package

simpletable.dataframe package#

Submodules#

simpletable.dataframe.dataframe module#

DataFrame class that is basically a wrapper around pandas.DataFrame which supports: - Column aliases - Units - Case sensitivity - search in the columns - inputs and outputs into various additional formats: FITS, CSV/Ascii, ECSV

class DataFrame[source]#

Bases: DataFrame

DataFrame class that is basically a wrapper around pandas.DataFrame which supports: - Column aliases - Units - Case sensitivity - search in the columns - preserve attrs information at initialization from DataFrame - inputs and outputs into various additional formats: FITS, CSV, ECSV

__init__(data, info=None, caseless=False)[source]#

Parameters:

data (ndarray[tuple[Any, ...], dtype[_ScalarT]] | Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] | Iterable | dict | DataFrame)
info (HeaderInfo | None)
caseless (bool)

property colnames: list[str]#

classmethod from_ascii(filepath_or_buffer, *, commented_header=False, **kwargs)[source]#

Read an ASCII file into a DataFrame.

from_csv with delimiter set to “ “ by default

Parameters:

filepath_or_buffer (str, path object or file-like object) – Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.csv.
commented_header (bool, default False) – Whether the header is commented or not.
**kwargs (dict) – Additional keyword arguments passed to pd.read_csv.

Returns:

DataFrame (pd.DataFrame) – The parsed data as a pd.DataFrame.
header (HeaderInfo) – The header information extracted from the file.

Return type:

DataFrame

See also

from_csv: Read a CSV file into a DataFrame

classmethod from_csv(filepath_or_buffer, *, commented_header=False, **kwargs)[source]#

Read a CSV file into a DataFrame while preserving header information

Equivalent to pd.read_csv with preserved header information.

Also supports optionally iterating or breaking of the file into chunks.

Additional help can be found in the online docs for IO Tools.

Parameters:

filepath_or_buffer (str, path object or file-like object) – Any valid string path is acceptable.
commented_header (bool, default False) – Whether the column definition header line starts with a comment character.
commentchar (str, default '#') – Character to treat as a comment character.
sep (str, default ',') – Character or regex pattern to treat as the delimiter. If sep=None, the C engine cannot automatically detect the separator, but the Python parsing engine can, meaning the latter will be used and automatically detect the separator from only the first valid row of the file by Python’s builtin sniffer tool, csv.Sniffer. In addition, separators longer than 1 character and different from '\s+' will be interpreted as regular expressions and will also force the use of the Python parsing engine. Note that regex delimiters are prone to ignoring quoted data. Regex example: '\r\t'.

Returns:

DataFrame (pd.DataFrame) – The parsed data as a pd.DataFrame.
header (HeaderInfo) – The header information extracted from the file.

Return type:

DataFrame

See also

from_ascii: Read a ASCII file into a DataFrame

classmethod from_ecsv(fname, **kwargs)[source]#

Read the content of an Enhanced Character Separated Values

Parameters:: fname (str) – The name of the file to read.
Returns:: data – The data read from the file. The chunked data read from the file.
Return type:: pd.DataFrame | Generator[pd.DataFrame, Any, None]

classmethod from_fits(filename, extension_number=1)[source]#

Load a DataFrame from a FITS file.

Parameters:

filename (str) – The path to the FITS file.
extension_number (int, optional) – The extension number to load, by default 1.

Returns:

The loaded DataFrame.

Return type:

DataFrame

classmethod from_votable(fname, *, table_index=0, is_url=False)[source]#

Read a VOTable file and return a pandas DataFrame and header information.

Parameters:

fname (str, bytes, IOBase, PathLike) – The filename or file-like object to read.
table_index (int, optional) – The index of the table to read, by default 0.
is_url (bool, optional) – Whether the file is a URL, by default False.

Returns:

df – Dataframe from VOTable file.

Return type:

DataFrame

property header: HeaderInfo#

info(header=False)[source]#

prints information on the table

Parameters:: header (bool, default False) – If True, print the header information.

keys(regexp=None, full_match=False, skip_aliases=False)[source]#

Return the data column names or a subset of it

Parameters:

regexp (str) – pattern to filter the keys with
full_match (bool) – if set, use re.fullmatch() instead of re.findall()
skip_aliases (bool) – include aliases if unset
string (Try to apply the pattern at the start of the)
returning
object (a match)
found. (or None if no match was)

Returns:

seq – sequence of keys

Return type:

sequence

property nbytes#: number of bytes of the object

property ncols: int#

property nrows: int#

pandas_info(verbose=None, buf=None, max_cols=None, memory_usage=None, show_counts=None)[source]#

Print a concise summary of a DataFrame.

This method prints information about a DataFrame including the index dtype and columns, non-null values and memory usage.

Parameters:

verbose (bool, optional) – Whether to print the full summary. By default, the setting in pandas.options.display.max_info_columns is followed.
buf (writable buffer, defaults to sys.stdout) – Where to send the output. By default, the output is printed to sys.stdout. Pass a writable buffer if you need to further process the output.
max_cols (int, optional) – When to switch from the verbose to the truncated output. If the DataFrame has more than max_cols columns, the truncated output is used. By default, the setting in pandas.options.display.max_info_columns is used.
memory_usage (bool, str, optional) –
Specifies whether total memory usage of the DataFrame elements (including the index) should be displayed. By default, this follows the pandas.options.display.memory_usage setting.

True always show memory usage. False never shows memory usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a memory estimation is made based in column dtype and number of rows assuming values consume the same memory amount for corresponding dtypes. With deep memory introspection, a real memory usage calculation is performed at the cost of computational resources. See the Frequently Asked Questions for more details.
show_counts (bool, optional) – Whether to show the non-null counts. By default, this is shown only if the DataFrame is smaller than pandas.options.display.max_info_rows and pandas.options.display.max_info_columns. A value of True always shows the counts, and False never shows the counts.

Returns:

This method prints a summary of a DataFrame and returns None.

Return type:

None

See also

DataFrame.describe: Generate descriptive statistics of DataFrame columns.
DataFrame.memory_usage: Memory usage of DataFrame columns.

resolve_alias(colname)[source]#

Resolve an alias to the actual column name

Parameters:: colname (str | bytes | Hashable | Any) – Name or alias of the column
Returns:: Actual column name or initial value if not found
Return type:: str | bytes | Hashable | Any

reverse_alias(colname)[source]#

Returns aliases of a given column

Parameters:: colname (str | bytes | Hashable | Any) – Name or alias of the column
Returns:: Actual column name or initial value if not found
Return type:: str | bytes | Hashable | Any

set_alias(alias, colname)[source]#

Set an alias for a column referenced by name or alias

Parameters:

alias (str)
colname (str)

Return type:

None

set_column_comment(colname, comment)[source]#

Set the comment for a column referenced by name or alias

Parameters:

colname (str) – Name or alias of the column
comment (str) – Comment to set for the column

set_column_unit(colname, unit)[source]#

Set the unit for a column referenced by name or alias

Parameters:

colname (str) – Name or alias of the column
unit (str) – Unit to set for the column

property shape: tuple[int, int]#

Return a tuple representing the dimensionality of the DataFrame.

See also

ndarray.shape: Tuple of array dimensions.

Examples

>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> df.shape
(2, 2)

>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4],
...                    'col3': [5, 6]})
>>> df.shape
(2, 3)

to_ascii(filepath_or_buffer, *, sep=' ', commentchar='#', **kwargs)#

Write object to an ASCII values file while preserving attrs

Equivalent to to_csv with default sep set to a space.

See also

to_csv: Write object to a CSV file while preserving attrs

Parameters:

self (DataFrame)
filepath_or_buffer (str | PathLike[str] | BaseBuffer)
sep (str)
commentchar (str)

Return type:

str | None

to_csv(filepath_or_buffer, *, sep=',', commentchar='#', 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='.', errors='strict', storage_options=None)#

Write object to a comma-separated values (csv) file while preserving attrs

Fallsback to pd.DataFrame.to_csv if no attrs content

Parameters:

path_or_buf (str, path object, file-like object, or None, default None) – 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’.
sep (str, default ',') – String of length 1. Field delimiter for the output file.
commentchar (str, default '#') – Character starting a comment line 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}.

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’.
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.).
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') – 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.
self (DataFrame)
filepath_or_buffer (str | PathLike[str] | BaseBuffer)
compression (Literal['infer', 'gzip', 'bz2', 'zip', 'xz', 'zstd', 'tar'] | dict[str, ~typing.Any] | None)

Returns:

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

Return type:

None or str

to_ecsv(df, fname, mode='w', **meta)[source]#

output data into ecsv file

Parameters:

df (pd.DataFrame) – data to be written to the file.
fname (str) – the name of the file to write.
mode (str) – the mode to open the file.
meta (dict) – meta data to be written to the header.

Return type:

None

to_fits(filename, header_info=None, output_verify='exception', checksum=False, index=True, overwrite=False, append=False, **kwargs)[source]#

Save a DataFrame to a FITS file.

Parameters:

filename (str) – The path to the FITS file.
header_info (HeaderInfo | None, optional) – Header information to save with the FITS file by default None and taken from data.attrs override data.attrs if provided
output_verify (str) – Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", +warn, or +exception" (e.g. ``"fix+warn"). See verify for more info.
checksum (bool, optional) – If True, adds both DATASUM and CHECKSUM cards to the headers of all HDU’s written to the file
index (bool, optional) – If True, includes the index in the FITS file. Default is True.
append (bool, optional) – If True, appends the DataFrame to the FITS file. Default is False.
overwrite (bool, optional) – If True, overwrites the DataFrame in the FITS file. Default is False.
**kwargs (dict) – Additional keyword arguments to pass to the FITS writer.

Return type:

None

testing()[source]#

simpletable.dataframe.header module#

class HeaderInfo[source]#

Bases: object

Extracted information from FITS header

header#

header dictionary

Type:: dict

alias#

aliases

Type:: dict

units#

units

Type:: dict

comments#

comments/description of keywords

Type:: dict

__init__(header, alias, units, comments)#

Parameters:

header (dict[Hashable, Any])
alias (dict[Hashable, str])
units (dict[Hashable, str])
comments (dict[Hashable, str])

Return type:

None

alias: dict[Hashable, str] = <dataclasses._MISSING_TYPE object>#

comments: dict[Hashable, str] = <dataclasses._MISSING_TYPE object>#

header: dict[Hashable, Any] = <dataclasses._MISSING_TYPE object>#

units: dict[Hashable, str] = <dataclasses._MISSING_TYPE object>#

simpletable.dataframe.helpers module#

pretty_size_print(num_bytes)[source]#

Output number of bytes in a human readable format

Parameters:: num_bytes (int) – number of bytes to convert
Returns:: output – string representation of the size with appropriate unit scale
Return type:: str

Module contents#

class DataFrame[source]#

Bases: DataFrame

__init__(data, info=None, caseless=False)[source]#

Parameters:

data (ndarray[tuple[Any, ...], dtype[_ScalarT]] | Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] | Iterable | dict | DataFrame)
info (HeaderInfo | None)
caseless (bool)

property colnames: list[str]#

classmethod from_ascii(filepath_or_buffer, *, commented_header=False, **kwargs)[source]#

Read an ASCII file into a DataFrame.

from_csv with delimiter set to “ “ by default

Parameters:

filepath_or_buffer (str, path object or file-like object) – Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.csv.
commented_header (bool, default False) – Whether the header is commented or not.
**kwargs (dict) – Additional keyword arguments passed to pd.read_csv.

Returns:

DataFrame (pd.DataFrame) – The parsed data as a pd.DataFrame.
header (HeaderInfo) – The header information extracted from the file.

Return type:

DataFrame

See also

from_csv: Read a CSV file into a DataFrame

classmethod from_csv(filepath_or_buffer, *, commented_header=False, **kwargs)[source]#

Read a CSV file into a DataFrame while preserving header information

Equivalent to pd.read_csv with preserved header information.

Also supports optionally iterating or breaking of the file into chunks.

Additional help can be found in the online docs for IO Tools.

Parameters:

filepath_or_buffer (str, path object or file-like object) – Any valid string path is acceptable.
commented_header (bool, default False) – Whether the column definition header line starts with a comment character.
commentchar (str, default '#') – Character to treat as a comment character.
sep (str, default ',') – Character or regex pattern to treat as the delimiter. If sep=None, the C engine cannot automatically detect the separator, but the Python parsing engine can, meaning the latter will be used and automatically detect the separator from only the first valid row of the file by Python’s builtin sniffer tool, csv.Sniffer. In addition, separators longer than 1 character and different from '\s+' will be interpreted as regular expressions and will also force the use of the Python parsing engine. Note that regex delimiters are prone to ignoring quoted data. Regex example: '\r\t'.

Returns:

DataFrame (pd.DataFrame) – The parsed data as a pd.DataFrame.
header (HeaderInfo) – The header information extracted from the file.

Return type:

DataFrame

See also

from_ascii: Read a ASCII file into a DataFrame

classmethod from_ecsv(fname, **kwargs)[source]#

Read the content of an Enhanced Character Separated Values

Parameters:: fname (str) – The name of the file to read.
Returns:: data – The data read from the file. The chunked data read from the file.
Return type:: pd.DataFrame | Generator[pd.DataFrame, Any, None]

classmethod from_fits(filename, extension_number=1)[source]#

Load a DataFrame from a FITS file.

Parameters:

filename (str) – The path to the FITS file.
extension_number (int, optional) – The extension number to load, by default 1.

Returns:

The loaded DataFrame.

Return type:

DataFrame

classmethod from_votable(fname, *, table_index=0, is_url=False)[source]#

Read a VOTable file and return a pandas DataFrame and header information.

Parameters:

fname (str, bytes, IOBase, PathLike) – The filename or file-like object to read.
table_index (int, optional) – The index of the table to read, by default 0.
is_url (bool, optional) – Whether the file is a URL, by default False.

Returns:

df – Dataframe from VOTable file.

Return type:

DataFrame

property header: HeaderInfo#

info(header=False)[source]#

prints information on the table

Parameters:: header (bool, default False) – If True, print the header information.

keys(regexp=None, full_match=False, skip_aliases=False)[source]#

Return the data column names or a subset of it

Parameters:

regexp (str) – pattern to filter the keys with
full_match (bool) – if set, use re.fullmatch() instead of re.findall()
skip_aliases (bool) – include aliases if unset
string (Try to apply the pattern at the start of the)
returning
object (a match)
found. (or None if no match was)

Returns:

seq – sequence of keys

Return type:

sequence

property nbytes#: number of bytes of the object

property ncols: int#

property nrows: int#

pandas_info(verbose=None, buf=None, max_cols=None, memory_usage=None, show_counts=None)[source]#

Print a concise summary of a DataFrame.

This method prints information about a DataFrame including the index dtype and columns, non-null values and memory usage.

Parameters:

verbose (bool, optional) – Whether to print the full summary. By default, the setting in pandas.options.display.max_info_columns is followed.
buf (writable buffer, defaults to sys.stdout) – Where to send the output. By default, the output is printed to sys.stdout. Pass a writable buffer if you need to further process the output.
max_cols (int, optional) – When to switch from the verbose to the truncated output. If the DataFrame has more than max_cols columns, the truncated output is used. By default, the setting in pandas.options.display.max_info_columns is used.
memory_usage (bool, str, optional) –
Specifies whether total memory usage of the DataFrame elements (including the index) should be displayed. By default, this follows the pandas.options.display.memory_usage setting.

True always show memory usage. False never shows memory usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a memory estimation is made based in column dtype and number of rows assuming values consume the same memory amount for corresponding dtypes. With deep memory introspection, a real memory usage calculation is performed at the cost of computational resources. See the Frequently Asked Questions for more details.
show_counts (bool, optional) – Whether to show the non-null counts. By default, this is shown only if the DataFrame is smaller than pandas.options.display.max_info_rows and pandas.options.display.max_info_columns. A value of True always shows the counts, and False never shows the counts.

Returns:

This method prints a summary of a DataFrame and returns None.

Return type:

None

See also

DataFrame.describe: Generate descriptive statistics of DataFrame columns.
DataFrame.memory_usage: Memory usage of DataFrame columns.

resolve_alias(colname)[source]#

Resolve an alias to the actual column name

Parameters:: colname (str | bytes | Hashable | Any) – Name or alias of the column
Returns:: Actual column name or initial value if not found
Return type:: str | bytes | Hashable | Any

reverse_alias(colname)[source]#

Returns aliases of a given column

Parameters:: colname (str | bytes | Hashable | Any) – Name or alias of the column
Returns:: Actual column name or initial value if not found
Return type:: str | bytes | Hashable | Any

set_alias(alias, colname)[source]#

Set an alias for a column referenced by name or alias

Parameters:

alias (str)
colname (str)

Return type:

None

set_column_comment(colname, comment)[source]#

Set the comment for a column referenced by name or alias

Parameters:

colname (str) – Name or alias of the column
comment (str) – Comment to set for the column

set_column_unit(colname, unit)[source]#

Set the unit for a column referenced by name or alias

Parameters:

colname (str) – Name or alias of the column
unit (str) – Unit to set for the column

property shape: tuple[int, int]#

Return a tuple representing the dimensionality of the DataFrame.

See also

ndarray.shape: Tuple of array dimensions.

Examples

>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
>>> df.shape
(2, 2)

>>> df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4],
...                    'col3': [5, 6]})
>>> df.shape
(2, 3)

to_ascii(filepath_or_buffer, *, sep=' ', commentchar='#', **kwargs)#

Write object to an ASCII values file while preserving attrs

Equivalent to to_csv with default sep set to a space.

See also

to_csv: Write object to a CSV file while preserving attrs

Parameters:

self (DataFrame)
filepath_or_buffer (str | PathLike[str] | BaseBuffer)
sep (str)
commentchar (str)

Return type:

str | None

Write object to a comma-separated values (csv) file while preserving attrs

Fallsback to pd.DataFrame.to_csv if no attrs content

Parameters:

path_or_buf (str, path object, file-like object, or None, default None) – 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’.
sep (str, default ',') – String of length 1. Field delimiter for the output file.
commentchar (str, default '#') – Character starting a comment line 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}.

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’.
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.).
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') – 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.
self (DataFrame)
filepath_or_buffer (str | PathLike[str] | BaseBuffer)
compression (Literal['infer', 'gzip', 'bz2', 'zip', 'xz', 'zstd', 'tar'] | dict[str, ~typing.Any] | None)

Returns:

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

Return type:

None or str

to_ecsv(df, fname, mode='w', **meta)[source]#

output data into ecsv file

Parameters:

df (pd.DataFrame) – data to be written to the file.
fname (str) – the name of the file to write.
mode (str) – the mode to open the file.
meta (dict) – meta data to be written to the header.

Return type:

None

to_fits(filename, header_info=None, output_verify='exception', checksum=False, index=True, overwrite=False, append=False, **kwargs)[source]#

Save a DataFrame to a FITS file.

Parameters:

filename (str) – The path to the FITS file.
header_info (HeaderInfo | None, optional) – Header information to save with the FITS file by default None and taken from data.attrs override data.attrs if provided
output_verify (str) – Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", +warn, or +exception" (e.g. ``"fix+warn"). See verify for more info.
checksum (bool, optional) – If True, adds both DATASUM and CHECKSUM cards to the headers of all HDU’s written to the file
index (bool, optional) – If True, includes the index in the FITS file. Default is True.
append (bool, optional) – If True, appends the DataFrame to the FITS file. Default is False.
overwrite (bool, optional) – If True, overwrites the DataFrame in the FITS file. Default is False.
**kwargs (dict) – Additional keyword arguments to pass to the FITS writer.

Return type:

None

simpletable.dataframe package

Contents

simpletable.dataframe package#

Subpackages#

Submodules#

simpletable.dataframe.dataframe module#

simpletable.dataframe.header module#

simpletable.dataframe.helpers module#

Module contents#