EventTable¶

class gwpy.table.EventTable(data=None, masked=None, names=None, dtype=None, meta=None, copy=True, rows=None, copy_indices=True, **kwargs)[source]¶

Bases: astropy.table.table.Table

A container for a table of events

This differs from the basic Table in two ways

• GW-specific file formats are registered to use with EventTable.read and EventTable.write
• columns of this table are of the EventColumn type, which provides methods for filtering based on a SegmentList (not specifically time segments)

See also

astropy.table.Table

for details on parameters for creating an EventTable

Methods Summary

add_column(col[, index, name, rename_duplicate])	Add a new Column object col to the table.
add_columns(cols[, indexes, names, copy, …])	Add a list of new Column objects cols to the table.
add_index(colnames[, engine, unique])	Insert a new index among one or more columns.
add_row([vals, mask])	Add a new row to the end of the table.
argsort([keys, kind])	Return the indices which would sort the table according to one or more key columns.
as_array([keep_byteorder])	Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).
binned_event_rates(stride, column, bins[, …])	Calculate an event rate TimeSeriesDict over a number of bins.
convert_bytestring_to_unicode([python3_only])	Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) assuming ASCII encoding.
convert_unicode_to_bytestring([python3_only])	Convert ASCII-only unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’).
copy([copy_data])	Return a copy of the table.
event_rate(stride[, start, end, timecolumn])	Calculate the rate TimeSeries for this Table.
fetch(format_, *args, **kwargs)	Fetch a table of events from a database
field(item)	Return column[item] for recarray compatibility.
filled([fill_value])	Return a copy of self, with masked values filled.
filter(*column_filters)	Apply one or more column slice filters to this EventTable
from_pandas(dataframe)	Create a Table from a pandas.DataFrame instance
get_column(name)	Return the Column with the given name
group_by(keys)	Group this table by the specified keys
hist(column, **kwargs)	Generate a HistogramPlot of this Table.
index_column(name)	Return the positional index of column name.
index_mode(mode)	Return a context manager for an indexing mode.
insert_row(index[, vals, mask])	Add a new row before the given index position in the table.
itercols()	Iterate over the columns of this table.
keep_columns(names)	Keep only the columns specified (remove the others).
keys()
more([max_lines, max_width, show_name, …])	Interactively browse table with a paging interface.
pformat([max_lines, max_width, show_name, …])	Return a list of lines for the formatted string representation of the table.
plot(x, y, *args, **kwargs)	Generate an EventTablePlot of this Table.
pprint([max_lines, max_width, show_name, …])	Print a formatted string representation of the table.
read(source, *args, **kwargs)	Read data into an EventTable
remove_column(name)	Remove a column from the table.
remove_columns(names)	Remove several columns from the table.
remove_indices(colname)	Remove all indices involving the given column.
remove_row(index)	Remove a row from the table.
remove_rows(row_specifier)	Remove rows from the table.
rename_column(name, new_name)	Rename a column.
replace_column(name, col)	Replace column name with the new col object.
reverse()	Reverse the row order of table rows.
show_in_browser([max_lines, jsviewer, …])	Render the table in HTML and show it in a web browser.
show_in_notebook([tableid, css, …])	Render the table in HTML and show it in the IPython notebook.
sort([keys])	Sort the table according to one or more keys.
to_pandas()	Return a pandas.DataFrame instance
write(target, *args, **kwargs)	Write this table to a file

Methods Documentation

add_column(col, index=None, name=None, rename_duplicate=False)¶

Add a new Column object col to the table. If index is supplied then insert column before index position in the list of columns, otherwise append column to the end of the list.

Parameters:	col : Column Column object to add. index : int or None Insert column before this position or at end (default). name : str Column name rename_duplicate : bool Uniquify column name if it already exist. Default is False.

Examples

Create a table with two columns ‘a’ and ‘b’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> print(t)
 a   b
--- ---
  1 0.1
  2 0.2
  3 0.3

Create a third column ‘c’ and append it to the end of the table:

>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> t.add_column(col_c)
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Add column ‘d’ at position 1. Note that the column is inserted before the given index:

>>> col_d = Column(name='d', data=['a', 'b', 'c'])
>>> t.add_column(col_d, 1)
>>> print(t)
 a   d   b   c
--- --- --- ---
  1   a 0.1   x
  2   b 0.2   y
  3   c 0.3   z

Add second column named ‘b’ with rename_duplicate:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_b = Column(name='b', data=[1.1, 1.2, 1.3])
>>> t.add_column(col_b, rename_duplicate=True)
>>> print(t)
 a   b  b_1
--- --- ---
  1 0.1 1.1
  2 0.2 1.2
  3 0.3 1.3

Add an unnamed column or mixin object in the table using a default name or by specifying an explicit name with name. Name can also be overridden:

>>> t = Table([[1, 2], [0.1, 0.2]], names=('a', 'b'))
>>> col_c = Column(data=['x', 'y'])
>>> t.add_column(col_c)
>>> t.add_column(col_c, name='c')
>>> col_b = Column(name='b', data=[1.1, 1.2])
>>> t.add_column(col_b, name='d')
>>> print(t)
 a   b  col2  c   d
--- --- ---- --- ---
  1 0.1    x   x 1.1
  2 0.2    y   y 1.2

To add several columns use add_columns.

add_columns(cols, indexes=None, names=None, copy=True, rename_duplicate=False)¶

Add a list of new Column objects cols to the table. If a corresponding list of indexes is supplied then insert column before each index position in the original list of columns, otherwise append columns to the end of the list.

Parameters:	cols : list of Columns Column objects to add. indexes : list of ints or None Insert column before this position or at end (default). names : list of str Column names copy : bool Make a copy of the new columns. Default is True. rename_duplicate : bool Uniquify new column names if they duplicate the existing ones. Default is False.

Examples

Create a table with two columns ‘a’ and ‘b’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> print(t)
 a   b
--- ---
  1 0.1
  2 0.2
  3 0.3

Create column ‘c’ and ‘d’ and append them to the end of the table:

>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> col_d = Column(name='d', data=['u', 'v', 'w'])
>>> t.add_columns([col_c, col_d])
>>> print(t)
 a   b   c   d
--- --- --- ---
  1 0.1   x   u
  2 0.2   y   v
  3 0.3   z   w

Add column ‘c’ at position 0 and column ‘d’ at position 1. Note that the columns are inserted before the given position:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> col_d = Column(name='d', data=['u', 'v', 'w'])
>>> t.add_columns([col_c, col_d], [0, 1])
>>> print(t)
 c   a   d   b
--- --- --- ---
  x   1   u 0.1
  y   2   v 0.2
  z   3   w 0.3

Add second column ‘b’ and column ‘c’ with rename_duplicate:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> col_b = Column(name='b', data=[1.1, 1.2, 1.3])
>>> col_c = Column(name='c', data=['x', 'y', 'z'])
>>> t.add_columns([col_b, col_c], rename_duplicate=True)
>>> print(t)
 a   b  b_1  c
--- --- --- ---
  1 0.1 1.1  x
  2 0.2 1.2  y
  3 0.3 1.3  z

Add unnamed columns or mixin objects in the table using default names or by specifying explicit names with names. Names can also be overridden:

>>> t = Table()
>>> col_a = Column(data=['x', 'y'])
>>> col_b = Column(name='b', data=['u', 'v'])
>>> t.add_columns([col_a, col_b])
>>> t.add_columns([col_a, col_b], names=['c', 'd'])
>>> print(t)
col0  b   c   d
---- --- --- ---
   x   u   x   u
   y   v   y   v

add_index(colnames, engine=None, unique=False)¶

Insert a new index among one or more columns. If there are no indices, make this index the primary table index.

Parameters:	colnames : str or list List of column names (or a single column name) to index engine : type or None Indexing engine class to use, from among SortedArray, BST, FastBST, and FastRBT. If the supplied argument is None (by default), use SortedArray. unique : bool Whether the values of the index must be unique. Default is False.

add_row(vals=None, mask=None)¶

Add a new row to the end of the table.

The vals argument can be:

sequence (e.g. tuple or list)

Column values in the same order as table columns.

mapping (e.g. dict)

Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.

None

All values filled with np.zeros for the column dtype.

This method requires that the Table object “owns” the underlying array data. In particular one cannot add a row to a Table that was initialized with copy=False from an existing array.

The mask attribute should give (if desired) the mask for the values. The type of the mask should match that of the values, i.e. if vals is an iterable, then mask should also be an iterable with the same length, and if vals is a mapping, then mask should be a dictionary.

Parameters:	vals : tuple, list, dict or None Use the specified values in the new row mask : tuple, list, dict or None Use the specified mask values in the new row

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1,2],[4,5],[7,8]], names=('a','b','c'))
>>> print(t)
 a   b   c
--- --- ---
  1   4   7
  2   5   8

Adding a new row with entries ‘3’ in ‘a’, ‘6’ in ‘b’ and ‘9’ in ‘c’:

>>> t.add_row([3,6,9])
>>> print(t)
  a   b   c
  --- --- ---
  1   4   7
  2   5   8
  3   6   9

argsort(keys=None, kind=None)¶

Return the indices which would sort the table according to one or more key columns. This simply calls the numpy.argsort function on the table with the order parameter set to keys.

Parameters:	keys : str or list of str The column name(s) to order the table by kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm.
Returns:	index_array : ndarray, int Array of indices that sorts the table by the specified key column(s).

as_array(keep_byteorder=False)¶

Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).

Parameters:	keep_byteorder : bool, optional By default the returned array has all columns in native byte order. However, if this option is True this preserves the byte order of all columns (if any are non-native).
Returns:	table_array : np.ndarray (unmasked) or np.ma.MaskedArray (masked) Copy of table as a numpy structured array

binned_event_rates(stride, column, bins, operator='>=', start=None, end=None, timecolumn='time')[source]¶

Calculate an event rate TimeSeriesDict over a number of bins.

Parameters:

stride : float size (seconds) of each time bin column : str name of column by which to bin. bins : list a list of tuples marking containing bins, or a list of floats defining bin edges against which an math operation is performed for each event. operator : str, callable one of: '<', '<=', '>', '>=', '==', '!=', for a standard mathematical operation, 'in' to use the list of bins as containing bin edges, or a callable function that takes compares an event value against the bin value and returns a boolean. Note If bins is given as a list of tuples, this argument is ignored. start : float, LIGOTimeGPS, optional GPS start epoch of rate TimeSeries. end : float, LIGOTimeGPS, optional GPS end time of rate TimeSeries. This value will be rounded up to the nearest sample if needed. timecolumn : str, optional, default: time name of time-column to use when binning events

Returns:

rates : ~gwpy.timeseries.TimeSeriesDict` a dict of (bin, TimeSeries) pairs describing a rate of events per second (Hz) for each of the bins.

convert_bytestring_to_unicode(python3_only=False)¶

Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) assuming ASCII encoding.

Internally this changes string columns to represent each character in the string with a 4-byte UCS-4 equivalent, so it is inefficient for memory but allows Python 3 scripts to manipulate string arrays with natural syntax.

The python3_only parameter is provided as a convenience so that code can be written in a Python 2 / 3 compatible way:

>>> t = Table.read('my_data.fits')
>>> t.convert_bytestring_to_unicode(python3_only=True)

Parameters:	python3_only : bool Only do this operation for Python 3

convert_unicode_to_bytestring(python3_only=False)¶

Convert ASCII-only unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’).

When exporting a unicode string array to a file in Python 3, it may be desirable to encode unicode columns as bytestrings. This routine takes advantage of numpy automated conversion which works for strings that are pure ASCII.

The python3_only parameter is provided as a convenience so that code can be written in a Python 2 / 3 compatible way:

>>> t.convert_unicode_to_bytestring(python3_only=True)
>>> t.write('my_data.fits')

Parameters:	python3_only : bool Only do this operation for Python 3

copy(copy_data=True)¶

Return a copy of the table.

Parameters:	copy_data : bool If True (the default), copy the underlying data array. Otherwise, use the same data array .. note:: The meta is always deepcopied regardless of the value for copy_data.

event_rate(stride, start=None, end=None, timecolumn='time')[source]¶

Calculate the rate TimeSeries for this Table.

Parameters:	stride : float size (seconds) of each time bin start : float, LIGOTimeGPS, optional GPS start epoch of rate TimeSeries end : float, LIGOTimeGPS, optional GPS end time of rate TimeSeries. This value will be rounded up to the nearest sample if needed. timecolumn : str, optional, default: time name of time-column to use when binning events
Returns:	rate : TimeSeries a TimeSeries of events per second (Hz)

classmethod fetch(format_, *args, **kwargs)[source]¶

Fetch a table of events from a database

Parameters:

format : str, Engine the format of the remote data, see _Notes_ for a list of registered formats, OR an SQL database Engine object *args all other positional arguments are specific to the data format, see below for basic usage columns : list of str, optional the columns to fetch from the database table, defaults to all selection : str, or list of str, optional one or more column filters with which to downselect the returned table rows as they as read, e.g. 'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as a list, e.g. 'snr > 5 && frequency < 1000' or ['snr > 5', 'frequency < 1000'] **kwargs all other positional arguments are specific to the data format, see the online documentation for more details

Returns:

table : EventTable a table of events recovered from the remote database

Notes

The available named formats are:

Format	Basic usage
gravityspy	fetch('gravityspy', tablename)
hacr	fetch('hacr', channel, gpsstart, gpstop)

Examples

>>> from gwpy.table import EventTable

To download a table of all blip glitches from the Gravity Spy database:

>>> EventTable.fetch('gravityspy', 'glitches', selection='Label=Blip')

To download a table from any SQL-type server

>>> from sqlalchemy.engine import create_engine
>>> engine = create_engine(...)
>>> EventTable.fetch(engine, 'mytable')

field(item)¶

Return column[item] for recarray compatibility.

filled(fill_value=None)¶

Return a copy of self, with masked values filled.

If input fill_value supplied then that value is used for all masked entries in the table. Otherwise the individual fill_value defined for each table column is used.

Parameters:	fill_value : str If supplied, this fill_value is used for all masked entries in the entire table.
Returns:	filled_table : Table New table with masked values filled

filter(*column_filters)[source]¶

Apply one or more column slice filters to this EventTable

Multiple column filters can be given, and will be applied concurrently

Parameters:	column_filter : str, tuple a column slice filter definition, e.g. 'snr > 10, or a filter tuple definition, e.g. ('snr', <my_func>, <arg>)
Returns:	table : EventTable a new table with only those rows matching the filters

Notes

See Filtering tables for more details on using filter tuples

Examples

To filter an existing EventTable (table) to include only rows with snr greater than 10, and frequency less than 1000:

>>> table.filter('snr>10', 'frequency<1000')

Custom operations can be defined using filter tuple definitions:

>>> from gwpy.table.filters import in_segmentlist
>>> filter(my_table, ('time', in_segmentlist, segs))

from_pandas(dataframe)¶

Create a Table from a pandas.DataFrame instance

Parameters:	dataframe : pandas.DataFrame The pandas pandas.DataFrame instance
Returns:	table : Table A Table (or subclass) instance

get_column(name)[source]¶

Return the Column with the given name

This method is provided only for compatibility with the glue.ligolw.table.Table.

Parameters:	name : str the name of the column to return
Returns:	column : astropy.table.Column
Raises:	KeyError if no column is found with the given name

group_by(keys)¶

Group this table by the specified keys

This effectively splits the table into groups which correspond to unique values of the keys grouping object. The output is a new TableGroups which contains a copy of this table but sorted by row according to keys.

The keys input to group_by can be specified in different ways:

• String or list of strings corresponding to table column name(s)
• Numpy array (homogeneous or structured) with same length as this table
• Table with same length as this table

Parameters:	keys : str, list of str, numpy array, or Table Key grouping object
Returns:	out : Table New table with groups set

hist(column, **kwargs)[source]¶

Generate a HistogramPlot of this Table.

Parameters:	column : str name of the column over which to histogram data **kwargs any other arguments applicable to the HistogramPlot
Returns:	plot : HistogramPlot new plot displaying a histogram of this Table.

index_column(name)¶

Return the positional index of column name.

Parameters:	name : str column name
Returns:	index : int Positional index of column name.

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Get index of column ‘b’ of the table:

>>> t.index_column('b')
1

index_mode(mode)¶

Return a context manager for an indexing mode.

Parameters:

mode : str Either ‘freeze’, ‘copy_on_getitem’, or ‘discard_on_copy’. In ‘discard_on_copy’ mode, indices are not copied whenever columns or tables are copied. In ‘freeze’ mode, indices are not modified whenever columns are modified; at the exit of the context, indices refresh themselves based on column values. This mode is intended for scenarios in which one intends to make many additions or modifications in an indexed column. In ‘copy_on_getitem’ mode, indices are copied when taking column slices as well as table slices, so col[i0:i1] will preserve indices.

insert_row(index, vals=None, mask=None)¶

Add a new row before the given index position in the table.

The vals argument can be:

sequence (e.g. tuple or list)

Column values in the same order as table columns.

mapping (e.g. dict)

Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.

None

All values filled with np.zeros for the column dtype.

The mask attribute should give (if desired) the mask for the values. The type of the mask should match that of the values, i.e. if vals is an iterable, then mask should also be an iterable with the same length, and if vals is a mapping, then mask should be a dictionary.

Parameters:	vals : tuple, list, dict or None Use the specified values in the new row mask : tuple, list, dict or None Use the specified mask values in the new row

itercols()¶

Iterate over the columns of this table.

Examples

To iterate over the columns of a table:

>>> t = Table([[1], [2]])
>>> for col in t.itercols():
...     print(col)
col0
----
   1
col1
----
   2

Using itercols() is similar to for col in t.columns.values() but is syntactically preferred.

keep_columns(names)¶

Keep only the columns specified (remove the others).

Parameters:	names : list A list containing the names of the columns to keep. All other columns will be removed.

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Specifying only a single column name keeps only this column. Keep only column ‘a’ of the table:

>>> t.keep_columns('a')
>>> print(t)
 a
---
  1
  2
  3

Specifying a list of column names is keeps is also possible. Keep columns ‘a’ and ‘c’ of the table:

>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> t.keep_columns(['a', 'c'])
>>> print(t)
 a   c
--- ---
  1   x
  2   y
  3   z

keys()¶

more(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False)¶

Interactively browse table with a paging interface.

Supported keys:

f, <space> : forward one page
b : back one page
r : refresh same page
n : next row
p : previous row
< : go to beginning
> : go to end
q : quit browsing
h : print this help

Parameters:

max_lines : int Maximum number of lines in table output max_width : int or None Maximum character width of output show_name : bool Include a header row for column names. Default is True. show_unit : bool Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit. show_dtype : bool Include a header row for column dtypes. Default is True.

pformat(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, html=False, tableid=None, align=None, tableclass=None)¶

Return a list of lines for the formatted string representation of the table.

If no value of max_lines is supplied then the height of the screen terminal is used to set max_lines. If the terminal height cannot be determined then the default is taken from the configuration item astropy.conf.max_lines. If a negative value of max_lines is supplied then there is no line limit applied.

The same applies for max_width except the configuration item is astropy.conf.max_width.

Parameters:

max_lines : int or None Maximum number of rows to output max_width : int or None Maximum character width of output show_name : bool Include a header row for column names. Default is True. show_unit : bool Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit. show_dtype : bool Include a header row for column dtypes. Default is True. html : bool Format the output as an HTML table. Default is False. tableid : str or None An ID tag for the table; only used if html is set. Default is “table{id}”, where id is the unique integer id of the table object, id(self) align : str or list or tuple or None Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns. tableclass : str or list of str or None CSS classes for the table; only used if html is set. Default is None.

Returns:

lines : list Formatted table as a list of strings.

plot(x, y, *args, **kwargs)[source]¶

Generate an EventTablePlot of this Table.

Parameters:

x : str name of column defining centre point on the X-axis y : str name of column defining centre point on the Y-axis width : str, optional name of column defining width of tile height : str, optional name of column defining height of tile Note The width and height positional arguments should either both be omitted, in which case a scatter plot will be drawn, or both given, in which case a collection of rectangles will be drawn. color : str, optional, default:None name of column by which to color markers **kwargs any other arguments applicable to the Plot constructor, and the Table plotter.

Returns:

plot : EventTablePlot new plot for displaying tabular data.

See also

matplotlib.pyplot.figure

for documentation of keyword arguments used to create the figure

matplotlib.figure.Figure.add_subplot

for documentation of keyword arguments used to create the axes

gwpy.plotter.EventTableAxes.plot_table

for documentation of keyword arguments used to display the table (calls out to scatter())

pprint(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, align=None)¶

Print a formatted string representation of the table.

If no value of max_lines is supplied then the height of the screen terminal is used to set max_lines. If the terminal height cannot be determined then the default is taken from the configuration item astropy.conf.max_lines. If a negative value of max_lines is supplied then there is no line limit applied.

The same applies for max_width except the configuration item is astropy.conf.max_width.

Parameters:

max_lines : int Maximum number of lines in table output. max_width : int or None Maximum character width of output. show_name : bool Include a header row for column names. Default is True. show_unit : bool Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit. show_dtype : bool Include a header row for column dtypes. Default is True. align : str or list or tuple or None Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.

classmethod read(source, *args, **kwargs)[source]¶

Read data into an EventTable

Parameters:	source : str, list, Cache file or list of files from which to read events *args other positional arguments will be passed directly to the underlying reader method for the given format format : str, optional the format of the given source files; if not given, an attempt will be made to automatically identify the format selection : str, or list of str one or more column filters with which to downselect the returned table rows as they as read, e.g. 'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as a list, e.g. 'snr > 5 && frequency < 1000' or ['snr > 5', 'frequency < 1000'] nproc : int, optional, default: 1 number of CPUs to use for parallel reading of multiple files verbose : bool, optional print a progress bar showing read status, default: False .. note:: Keyword arguments other than those listed here may be required depending on the format
Returns:	table : EventTable
Raises:	astropy.io.registry.IORegistryError if the format cannot be automatically identified

Notes

The available built-in formats are:

Format	Read	Write	Auto-identify
ascii.cwb	Yes	No	No
ascii.omega	Yes	No	No
gwf	Yes	No	No
hdf5.pycbc_live	Yes	No	Yes
ligolw	Yes	Yes	Yes
root	Yes	Yes	Yes
root.cwb	Yes	No	No
root.omicron	Yes	No	No

remove_column(name)¶

Remove a column from the table.

This can also be done with:

del table[name]

Parameters:	name : str Name of column to remove

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Remove column ‘b’ from the table:

>>> t.remove_column('b')
>>> print(t)
 a   c
--- ---
  1   x
  2   y
  3   z

To remove several columns at the same time use remove_columns.

remove_columns(names)¶

Remove several columns from the table.

Parameters:	names : list A list containing the names of the columns to remove

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...     names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Remove columns ‘b’ and ‘c’ from the table:

>>> t.remove_columns(['b', 'c'])
>>> print(t)
 a
---
  1
  2
  3

Specifying only a single column also works. Remove column ‘b’ from the table:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...     names=('a', 'b', 'c'))
>>> t.remove_columns('b')
>>> print(t)
 a   c
--- ---
  1   x
  2   y
  3   z

This gives the same as using remove_column.

remove_indices(colname)¶

Remove all indices involving the given column. If the primary index is removed, the new primary index will be the most recently added remaining index.

Parameters:	colname : str Name of column

remove_row(index)¶

Remove a row from the table.

Parameters:	index : int Index of row to remove

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Remove row 1 from the table:

>>> t.remove_row(1)
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  3 0.3   z

To remove several rows at the same time use remove_rows.

remove_rows(row_specifier)¶

Remove rows from the table.

Parameters:	row_specifier : slice, int, or array of ints Specification for rows to remove

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

Remove rows 0 and 2 from the table:

>>> t.remove_rows([0, 2])
>>> print(t)
 a   b   c
--- --- ---
  2 0.2   y

Note that there are no warnings if the slice operator extends outside the data:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']],
...           names=('a', 'b', 'c'))
>>> t.remove_rows(slice(10, 20, 1))
>>> print(t)
 a   b   c
--- --- ---
  1 0.1   x
  2 0.2   y
  3 0.3   z

rename_column(name, new_name)¶

Rename a column.

This can also be done directly with by setting the name attribute for a column:

table[name].name = new_name

TODO: this won’t work for mixins

Parameters:	name : str The current name of the column. new_name : str The new name for the column

Examples

Create a table with three columns ‘a’, ‘b’ and ‘c’:

>>> t = Table([[1,2],[3,4],[5,6]], names=('a','b','c'))
>>> print(t)
 a   b   c
--- --- ---
  1   3   5
  2   4   6

Renaming column ‘a’ to ‘aa’:

>>> t.rename_column('a' , 'aa')
>>> print(t)
 aa  b   c
--- --- ---
  1   3   5
  2   4   6

replace_column(name, col)¶

Replace column name with the new col object.

Parameters:	name : str Name of column to replace col : column object (list, ndarray, Column, etc) New column object to replace the existing column

Examples

Replace column ‘a’ with a float version of itself:

>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b'))
>>> float_a = t['a'].astype(float)
>>> t.replace_column('a', float_a)

reverse()¶

Reverse the row order of table rows. The table is reversed in place and there are no function arguments.

Examples

Create a table with three columns:

>>> t = Table([['Max', 'Jo', 'John'], ['Miller','Miller','Jackson'],
...         [12,15,18]], names=('firstname','name','tel'))
>>> print(t)
firstname   name  tel
--------- ------- ---
      Max  Miller  12
       Jo  Miller  15
     John Jackson  18

Reversing order:

>>> t.reverse()
>>> print(t)
firstname   name  tel
--------- ------- ---
     John Jackson  18
       Jo  Miller  15
      Max  Miller  12

show_in_browser(max_lines=5000, jsviewer=False, browser=u'default', jskwargs={u'use_local_files': True}, tableid=None, table_class=u'display compact', css=None, show_row_index=u'idx')¶

Render the table in HTML and show it in a web browser.

Parameters:

max_lines : int Maximum number of rows to export to the table (set low by default to avoid memory issues, since the browser view requires duplicating the table in memory). A negative value of max_lines indicates no row limit. jsviewer : bool If True, prepends some javascript headers so that the table is rendered as a DataTables data table. This allows in-browser searching & sorting. browser : str Any legal browser name, e.g. 'firefox', 'chrome', 'safari' (for mac, you may need to use 'open -a "/Applications/Google Chrome.app" {}' for Chrome). If 'default', will use the system default browser. jskwargs : dict Passed to the astropy.table.JSViewer init. Defaults to {'use_local_files': True} which means that the JavaScript libraries will be served from local copies. tableid : str or None An html ID tag for the table. Default is table{id}, where id is the unique integer id of the table object, id(self). table_class : str or None A string with a list of HTML classes used to style the table. Default is “display compact”, and other possible values can be found in http://www.datatables.net/manual/styling/classes css : string A valid CSS string declaring the formatting for the table. Defaults to astropy.table.jsviewer.DEFAULT_CSS. show_row_index : str or False If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.

show_in_notebook(tableid=None, css=None, display_length=50, table_class=u'astropy-default', show_row_index=u'idx')¶

Render the table in HTML and show it in the IPython notebook.

Parameters:

tableid : str or None An html ID tag for the table. Default is table{id}-XXX, where id is the unique integer id of the table object, id(self), and XXX is a random number to avoid conflicts when printing the same table multiple times. table_class : str or None A string with a list of HTML classes used to style the table. The special default string (‘astropy-default’) means that the string will be retrieved from the configuration item astropy.table.default_notebook_table_class. Note that these table classes may make use of bootstrap, as this is loaded with the notebook. See this page for the list of classes. css : string A valid CSS string declaring the formatting for the table. Defaults to astropy.table.jsviewer.DEFAULT_CSS_NB. display_length : int, optional Number or rows to show. Defaults to 50. show_row_index : str or False If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.

Notes

Currently, unlike show_in_browser (with jsviewer=True), this method needs to access online javascript code repositories. This is due to modern browsers’ limitations on accessing local files. Hence, if you call this method while offline (and don’t have a cached version of jquery and jquery.dataTables), you will not get the jsviewer features.

sort(keys=None)¶

Sort the table according to one or more keys. This operates on the existing table and does not return a new table.

Parameters:	keys : str or list of str The key(s) to order the table by. If None, use the primary index of the Table.

Examples

Create a table with 3 columns:

>>> t = Table([['Max', 'Jo', 'John'], ['Miller','Miller','Jackson'],
...         [12,15,18]], names=('firstname','name','tel'))
>>> print(t)
firstname   name  tel
--------- ------- ---
      Max  Miller  12
       Jo  Miller  15
     John Jackson  18

Sorting according to standard sorting rules, first ‘name’ then ‘firstname’:

>>> t.sort(['name','firstname'])
>>> print(t)
firstname   name  tel
--------- ------- ---
     John Jackson  18
       Jo  Miller  15
      Max  Miller  12

to_pandas()¶

Return a pandas.DataFrame instance

Returns:	dataframe : pandas.DataFrame A pandas pandas.DataFrame instance
Raises:	ImportError If pandas is not installed ValueError If the Table contains mixin or multi-dimensional columns

write(target, *args, **kwargs)[source]¶

Write this table to a file

Parameters:

target: `str` filename for output data file *args other positional arguments will be passed directly to the underlying writer method for the given format format : str, optional format for output data; if not given, an attempt will be made to automatically identify the format based on the target filename **kwargs other keyword arguments will be passed directly to the underlying writer method for the given format

Raises:

astropy.io.registry.IORegistryError if the format cannot be automatically identified

Notes

The available built-in formats are:

Format	Read	Write	Auto-identify
gwf	Yes	Yes	No
ligolw	Yes	Yes	Yes
root	Yes	Yes	Yes

Column[source]¶

alias of EventColumn

binned_event_rates(stride, column, bins, operator='>=', start=None, end=None, timecolumn='time')[source]

Calculate an event rate TimeSeriesDict over a number of bins.

Parameters:

stride : float size (seconds) of each time bin column : str name of column by which to bin. bins : list a list of tuples marking containing bins, or a list of floats defining bin edges against which an math operation is performed for each event. operator : str, callable one of: '<', '<=', '>', '>=', '==', '!=', for a standard mathematical operation, 'in' to use the list of bins as containing bin edges, or a callable function that takes compares an event value against the bin value and returns a boolean. Note If bins is given as a list of tuples, this argument is ignored. start : float, LIGOTimeGPS, optional GPS start epoch of rate TimeSeries. end : float, LIGOTimeGPS, optional GPS end time of rate TimeSeries. This value will be rounded up to the nearest sample if needed. timecolumn : str, optional, default: time name of time-column to use when binning events

Returns:

rates : ~gwpy.timeseries.TimeSeriesDict` a dict of (bin, TimeSeries) pairs describing a rate of events per second (Hz) for each of the bins.

event_rate(stride, start=None, end=None, timecolumn='time')[source]

Calculate the rate TimeSeries for this Table.

Parameters:	stride : float size (seconds) of each time bin start : float, LIGOTimeGPS, optional GPS start epoch of rate TimeSeries end : float, LIGOTimeGPS, optional GPS end time of rate TimeSeries. This value will be rounded up to the nearest sample if needed. timecolumn : str, optional, default: time name of time-column to use when binning events
Returns:	rate : TimeSeries a TimeSeries of events per second (Hz)

classmethod fetch(format_, *args, **kwargs)[source]

Fetch a table of events from a database

Parameters:

format : str, Engine the format of the remote data, see _Notes_ for a list of registered formats, OR an SQL database Engine object *args all other positional arguments are specific to the data format, see below for basic usage columns : list of str, optional the columns to fetch from the database table, defaults to all selection : str, or list of str, optional one or more column filters with which to downselect the returned table rows as they as read, e.g. 'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as a list, e.g. 'snr > 5 && frequency < 1000' or ['snr > 5', 'frequency < 1000'] **kwargs all other positional arguments are specific to the data format, see the online documentation for more details

Returns:

table : EventTable a table of events recovered from the remote database

Notes

The available named formats are:

Format	Basic usage
gravityspy	fetch('gravityspy', tablename)
hacr	fetch('hacr', channel, gpsstart, gpstop)

Examples

>>> from gwpy.table import EventTable

To download a table of all blip glitches from the Gravity Spy database:

>>> EventTable.fetch('gravityspy', 'glitches', selection='Label=Blip')

To download a table from any SQL-type server

>>> from sqlalchemy.engine import create_engine
>>> engine = create_engine(...)
>>> EventTable.fetch(engine, 'mytable')

filter(*column_filters)[source]

Apply one or more column slice filters to this EventTable

Multiple column filters can be given, and will be applied concurrently

Parameters:	column_filter : str, tuple a column slice filter definition, e.g. 'snr > 10, or a filter tuple definition, e.g. ('snr', <my_func>, <arg>)
Returns:	table : EventTable a new table with only those rows matching the filters

Notes

See Filtering tables for more details on using filter tuples

Examples

To filter an existing EventTable (table) to include only rows with snr greater than 10, and frequency less than 1000:

>>> table.filter('snr>10', 'frequency<1000')

Custom operations can be defined using filter tuple definitions:

>>> from gwpy.table.filters import in_segmentlist
>>> filter(my_table, ('time', in_segmentlist, segs))

get_column(name)[source]

Return the Column with the given name

This method is provided only for compatibility with the glue.ligolw.table.Table.

Parameters:	name : str the name of the column to return
Returns:	column : astropy.table.Column
Raises:	KeyError if no column is found with the given name

hist(column, **kwargs)[source]

Generate a HistogramPlot of this Table.

Parameters:	column : str name of the column over which to histogram data **kwargs any other arguments applicable to the HistogramPlot
Returns:	plot : HistogramPlot new plot displaying a histogram of this Table.

plot(x, y, *args, **kwargs)[source]

Generate an EventTablePlot of this Table.

Parameters:

x : str name of column defining centre point on the X-axis y : str name of column defining centre point on the Y-axis width : str, optional name of column defining width of tile height : str, optional name of column defining height of tile Note The width and height positional arguments should either both be omitted, in which case a scatter plot will be drawn, or both given, in which case a collection of rectangles will be drawn. color : str, optional, default:None name of column by which to color markers **kwargs any other arguments applicable to the Plot constructor, and the Table plotter.

Returns:

plot : EventTablePlot new plot for displaying tabular data.

See also

matplotlib.pyplot.figure

for documentation of keyword arguments used to create the figure

matplotlib.figure.Figure.add_subplot

for documentation of keyword arguments used to create the axes

gwpy.plotter.EventTableAxes.plot_table

for documentation of keyword arguments used to display the table (calls out to scatter())

classmethod read(source, *args, **kwargs)[source]

Read data into an EventTable

Parameters:	source : str, list, Cache file or list of files from which to read events *args other positional arguments will be passed directly to the underlying reader method for the given format format : str, optional the format of the given source files; if not given, an attempt will be made to automatically identify the format selection : str, or list of str one or more column filters with which to downselect the returned table rows as they as read, e.g. 'snr > 5'; multiple selections should be connected by ‘ && ‘, or given as a list, e.g. 'snr > 5 && frequency < 1000' or ['snr > 5', 'frequency < 1000'] nproc : int, optional, default: 1 number of CPUs to use for parallel reading of multiple files verbose : bool, optional print a progress bar showing read status, default: False .. note:: Keyword arguments other than those listed here may be required depending on the format
Returns:	table : EventTable
Raises:	astropy.io.registry.IORegistryError if the format cannot be automatically identified

Notes

The available built-in formats are:

Format	Read	Write	Auto-identify
ascii.cwb	Yes	No	No
ascii.omega	Yes	No	No
gwf	Yes	No	No
hdf5.pycbc_live	Yes	No	Yes
ligolw	Yes	Yes	Yes
root	Yes	Yes	Yes
root.cwb	Yes	No	No
root.omicron	Yes	No	No

write(target, *args, **kwargs)[source]

Write this table to a file

Parameters:

target: `str` filename for output data file *args other positional arguments will be passed directly to the underlying writer method for the given format format : str, optional format for output data; if not given, an attempt will be made to automatically identify the format based on the target filename **kwargs other keyword arguments will be passed directly to the underlying writer method for the given format

Raises:

astropy.io.registry.IORegistryError if the format cannot be automatically identified

Notes

The available built-in formats are:

Format	Read	Write	Auto-identify
gwf	Yes	Yes	No
ligolw	Yes	Yes	Yes
root	Yes	Yes	Yes