TimeSeries#
- class astropy.timeseries.TimeSeries(data=None, *, time=None, time_start=None, time_delta=None, n_samples=None, **kwargs)[source]#
Bases:
BaseTimeSeries
A class to represent time series data in tabular form.
TimeSeries
provides a class for representing time series as a collection of values of different quantities measured at specific points in time (for time series with finite time bins, see theBinnedTimeSeries
class).TimeSeries
is a sub-class ofQTable
and thus provides all the standard table maniplation methods available to tables, but it also provides additional conveniences for dealing with time series, such as a flexible initializer for setting up the times, a method for folding time series, and atime
attribute for easy access to the time values.See also: https://docs.astropy.org/en/stable/timeseries/
- Parameters:
- data
numpy
ndarray
,dict
,list
,Table
, or astropy:table-likeobject
, optional Data to initialize time series. This does not need to contain the times, which can be provided separately, but if it does contain the times they should be in a column called
'time'
to be automatically recognized.- time
Time
,TimeDelta
or iterable The times at which the values are sampled - this can be either given directly as a
Time
orTimeDelta
array or as any iterable that initializes theTime
class. If this is given, then the remaining time-related arguments should not be used.- time_start
Time
orstr
The time of the first sample in the time series. This is an alternative to providing
time
and requires thattime_delta
is also provided.- time_delta
TimeDelta
orQuantity
[:ref: ‘time’] The step size in time for the series. This can either be a scalar if the time series is evenly sampled, or an array of values if it is not.
- n_samples
int
The number of time samples for the series. This is only used if both
time_start
andtime_delta
are provided and are scalar values.- **kwargs
dict
, optional Additional keyword arguments are passed to
QTable
.
- data
Attributes Summary
True if table has any
MaskedColumn
columns.True if column in the table has values which are masked.
True if table has any mixin columns (defined as columns that are not Column subclasses).
Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index.
Return the indices associated with columns of the table as a TableIndices object.
Return a TableLoc object that can be used for retrieving rows by index in a given data range.
Return a TableLocIndices object that can be used for retrieving the row indices corresponding to given table index key value or values.
Maintain tuple that controls table column visibility for print output.
Maintain tuple that controls table column visibility for print output.
The time values.
Write this Table object out in the specified format.
Methods Summary
add_column
(*args, **kwargs)See
add_column()
.add_columns
(*args, **kwargs)See
add_columns()
.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, reverse])Return the indices which would sort the table according to one or more key columns.
as_array
([keep_byteorder, names])Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).
Convert bytestring columns (dtype.kind='S') to unicode (dtype.kind='U') using UTF-8 encoding.
Convert unicode columns (dtype.kind='U') to bytestring (dtype.kind='S') using UTF-8 encoding.
copy
([copy_data])Return a copy of the table.
field
(item)Return column[item] for recarray compatibility.
filled
([fill_value])Return copy of self, with masked values filled.
fold
([period, epoch_time, epoch_phase, ...])Return a new
TimeSeries
folded with a period and epoch.from_pandas
(df[, time_scale])Convert a
DataFrame
to aastropy.timeseries.TimeSeries
.group_by
(keys)Group this table by the specified
keys
.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.items
()itercols
()Iterate over the columns of this table.
iterrows
(*names)Iterate over rows of table returning a tuple of values for each row.
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
pformat_all
([max_lines, max_width, ...])Return a list of lines for the formatted string representation of
pprint
([max_lines, max_width, show_name, ...])Print a formatted string representation of the table.
pprint_all
([max_lines, max_width, ...])Print a formatted string representation of the entire table.
read
(filename[, time_column, time_format, ...])Read and parse a file and returns a
astropy.timeseries.TimeSeries
.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.
rename_columns
(names, new_names)Rename multiple columns.
replace_column
(name, col[, copy])Replace column
name
with the newcol
object.reverse
()Reverse the row order of table rows.
round
([decimals])Round numeric columns in-place to the specified number of decimals.
setdefault
(name, default)Ensure a column named
name
exists.show_in_browser
([max_lines, jsviewer, ...])show_in_notebook
([tableid, css, ...])sort
([keys, kind, reverse])Sort the table according to one or more keys.
Convert this
TimeSeries
to aDataFrame
with aDatetimeIndex
index.update
(other[, copy])Perform a dictionary-style update and merge metadata.
values
()values_equal
(other)Element-wise comparison of table with another table, list, or scalar.
Attributes Documentation
- ColumnClass#
- colnames#
- dtype#
- groups#
- has_masked_columns#
True if table has any
MaskedColumn
columns.This does not check for mixin columns that may have masked values, use the
has_masked_values
property in that case.
- has_masked_values#
True if column in the table has values which are masked.
This may be relatively slow for large tables as it requires checking the mask values of each column.
- has_mixin_columns#
True if table has any mixin columns (defined as columns that are not Column subclasses).
- iloc#
Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index.
- indices#
Return the indices associated with columns of the table as a TableIndices object.
- info#
- loc#
Return a TableLoc object that can be used for retrieving rows by index in a given data range. Note that both loc and iloc work only with single-column indices.
- loc_indices#
Return a TableLocIndices object that can be used for retrieving the row indices corresponding to given table index key value or values.
- mask#
- masked#
- meta = None#
- pprint_exclude_names#
Maintain tuple that controls table column visibility for print output.
This is a descriptor that inherits from MetaAttribute so that the attribute value is stored in the table meta[‘__attributes__’].
This gets used for the
pprint_include_names
andpprint_exclude_names
Table attributes.
- pprint_include_names#
Maintain tuple that controls table column visibility for print output.
This is a descriptor that inherits from MetaAttribute so that the attribute value is stored in the table meta[‘__attributes__’].
This gets used for the
pprint_include_names
andpprint_exclude_names
Table attributes.
- time#
The time values.
- write#
Write this Table object out in the specified format.
This function provides the Table interface to the astropy unified I/O layer. This allows easily writing a file in many supported data formats using syntax such as:
>>> from astropy.table import Table >>> dat = Table([[1, 2], [3, 4]], names=('a', 'b')) >>> dat.write('table.dat', format='ascii')
Get help on the available writers for
Table
using the``help()`` method:>>> Table.write.help() # Get help writing Table and list supported formats >>> Table.write.help('fits') # Get detailed help on Table FITS writer >>> Table.write.list_formats() # Print list of available formats
The
serialize_method
argument is explained in the section on Table serialization methods.See also: https://docs.astropy.org/en/stable/io/unified.html
- Parameters:
- *args
tuple
, optional Positional arguments passed through to data writer. If supplied the first argument is the output filename.
- format
str
File format specifier.
- serialize_method
str
,dict
, optional Serialization method specifier for columns.
- **kwargs
dict
, optional Keyword arguments passed through to data writer.
- *args
Methods Documentation
- add_column(*args, **kwargs)[source]#
See
add_column()
.
- add_columns(*args, **kwargs)[source]#
See
add_columns()
.
- 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
orlist
List of column names (or a single column name) to index
- enginetype or
None
Indexing engine class to use, either
SortedArray
,BST
, orSCEngine
. If the supplied argument is None (by default), useSortedArray
.- uniquebool
Whether the values of the index must be unique. Default is False.
- colnames
- 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. ifvals
is an iterable, thenmask
should also be an iterable with the same length, and ifvals
is a mapping, thenmask
should be a dictionary.- Parameters:
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, reverse=False)#
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 theorder
parameter set tokeys
.- Parameters:
- Returns:
- as_array(keep_byteorder=False, names=None)#
Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).
- Parameters:
- keep_byteorderbool, 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).- names
list
, optional: List of column names to include for returned structured array. Default is to include all table columns.
- Returns:
- table_array
array
orMaskedArray
Copy of table as a numpy structured array. ndarray for unmasked or
MaskedArray
for masked.
- table_array
- convert_bytestring_to_unicode()#
Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) using UTF-8 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 scripts to manipulate string arrays with natural syntax.
- convert_unicode_to_bytestring()#
Convert unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’) using UTF-8 encoding.
When exporting a unicode string array to a file, it may be desirable to encode unicode columns as bytestrings.
- copy(copy_data=True)#
Return a copy of the table.
- field(item)#
Return column[item] for recarray compatibility.
- filled(fill_value=None)#
Return 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 individualfill_value
defined for each table column is used.
- fold(period=None, epoch_time=None, epoch_phase=0, wrap_phase=None, normalize_phase=False)[source]#
Return a new
TimeSeries
folded with a period and epoch.- Parameters:
- period
Quantity
[:ref: ‘time’] The period to use for folding
- epoch_time
Time
The time to use as the reference epoch, at which the relative time offset / phase will be
epoch_phase
. Defaults to the first time in the time series.- epoch_phase
float
orQuantity
[:ref: ‘dimensionless’, :ref: ‘time’] Phase of
epoch_time
. Ifnormalize_phase
isTrue
, this should be a dimensionless value, while ifnormalize_phase
isFalse
, this should be aQuantity
with time units. Defaults to 0.- wrap_phase
float
orQuantity
[:ref: ‘dimensionless’, :ref: ‘time’] The value of the phase above which values are wrapped back by one period. If
normalize_phase
isTrue
, this should be a dimensionless value, while ifnormalize_phase
isFalse
, this should be aQuantity
with time units. Defaults to half the period, so that the resulting time series goes from-period / 2
toperiod / 2
(ifnormalize_phase
isFalse
) or -0.5 to 0.5 (ifnormalize_phase
isTrue
).- normalize_phasebool
If
False
phase is returned asTimeDelta
, otherwise as a dimensionlessQuantity
.
- period
- Returns:
- folded_timeseries
TimeSeries
The folded time series object with phase as the
time
column.
- folded_timeseries
- classmethod from_pandas(df, time_scale='utc')[source]#
Convert a
DataFrame
to aastropy.timeseries.TimeSeries
.- Parameters:
- df
pandas.DataFrame
A pandas
pandas.DataFrame
instance.- time_scale
str
The time scale to pass into
astropy.time.Time
. Defaults toUTC
.
- df
- 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 newTableGroups
which contains a copy of this table but sorted by row according tokeys
.The
keys
input togroup_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
- index_column(name)#
Return the 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.
- mode
- 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. ifvals
is an iterable, thenmask
should also be an iterable with the same length, and ifvals
is a mapping, thenmask
should be a dictionary.
- items()#
- 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 tofor col in t.columns.values()
but is syntactically preferred.
- iterrows(*names)#
Iterate over rows of table returning a tuple of values for each row.
This method is especially useful when only a subset of columns are needed.
The
iterrows
method can be substantially faster than using the standard Table row iteration (e.g.for row in tbl:
), since that returns a new~astropy.table.Row
object for each row and accessing a column in that row (e.g.row['col0']
) is slower than tuple access.- Parameters:
- names
list
List of column names (default to all columns if no names provided)
- names
- Returns:
- rowsiterable
Iterator returns tuples of row values
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table({'a': [1, 2, 3], ... 'b': [1.0, 2.5, 3.0], ... 'c': ['x', 'y', 'z']})
To iterate row-wise using column names:
>>> for a, c in t.iterrows('a', 'c'): ... print(a, c) 1 x 2 y 3 z
- keep_columns(names)#
Keep only the columns specified (remove the others).
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
Keep only column ‘a’ of the table:
>>> t.keep_columns('a') >>> print(t) a --- 1 2 3
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
orNone
Maximum character width of output
- show_namebool
Include a header row for column names. Default is True.
- show_unitbool
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_dtypebool
Include a header row for column dtypes. Default is False.
- max_lines
- 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 setmax_lines
. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines
. If a negative value ofmax_lines
is supplied then there is no line limit applied.The same applies for
max_width
except the configuration item isastropy.conf.max_width
.
- Parameters:
- max_lines
int
orNone
Maximum number of rows to output
- max_width
int
orNone
Maximum character width of output
- show_namebool
Include a header row for column names. Default is True.
- show_unitbool
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_dtypebool
Include a header row for column dtypes. Default is True.
- htmlbool
Format the output as an HTML table. Default is False.
- tableid
str
orNone
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
orlist
ortuple
orNone
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
orlist
ofstr
orNone
CSS classes for the table; only used if html is set. Default is None.
- max_lines
- Returns:
- lines
list
Formatted table as a list of strings.
- lines
- pformat_all(max_lines=-1, max_width=-1, 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 entire table.
If no value of
max_lines
is supplied then the height of the screen terminal is used to setmax_lines
. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines
. If a negative value ofmax_lines
is supplied then there is no line limit applied.The same applies for
max_width
except the configuration item isastropy.conf.max_width
.
- Parameters:
- max_lines
int
orNone
Maximum number of rows to output
- max_width
int
orNone
Maximum character width of output
- show_namebool
Include a header row for column names. Default is True.
- show_unitbool
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_dtypebool
Include a header row for column dtypes. Default is True.
- htmlbool
Format the output as an HTML table. Default is False.
- tableid
str
orNone
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
orlist
ortuple
orNone
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
orlist
ofstr
orNone
CSS classes for the table; only used if html is set. Default is None.
- max_lines
- Returns:
- lines
list
Formatted table as a list of strings.
- lines
- 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 setmax_lines
. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines
. If a negative value ofmax_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
orNone
Maximum number of lines in table output.
- max_width
int
orNone
Maximum character width of output.
- show_namebool
Include a header row for column names. Default is True.
- show_unitbool
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_dtypebool
Include a header row for column dtypes. Default is False.
- align
str
orlist
ortuple
orNone
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.
- max_lines
- pprint_all(max_lines=-1, max_width=-1, show_name=True, show_unit=None, show_dtype=False, align=None)#
Print a formatted string representation of the entire table.
This method is the same as
astropy.table.Table.pprint
except that the defaultmax_lines
andmax_width
are both -1 so that by default the entire table is printed instead of restricting to the size of the screen terminal.- Parameters:
- max_lines
int
orNone
Maximum number of lines in table output.
- max_width
int
orNone
Maximum character width of output.
- show_namebool
Include a header row for column names. Default is True.
- show_unitbool
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_dtypebool
Include a header row for column dtypes. Default is False.
- align
str
orlist
ortuple
orNone
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.
- max_lines
- classmethod read(filename, time_column=None, time_format=None, time_scale=None, format=None, *args, **kwargs)[source]#
Read and parse a file and returns a
astropy.timeseries.TimeSeries
.This method uses the unified I/O infrastructure in Astropy which makes it easy to define readers/writers for various classes (https://docs.astropy.org/en/stable/io/unified.html). By default, this method will try and use readers defined specifically for the
astropy.timeseries.TimeSeries
class - however, it is also possible to use theformat
keyword to specify formats defined for theastropy.table.Table
class - in this case, you will need to also provide the column names for column containing the start times for the bins, as well as other column names (see the Parameters section below for details):>>> from astropy.timeseries import TimeSeries >>> ts = TimeSeries.read('sampled.dat', format='ascii.ecsv', ... time_column='date')
- Parameters:
- filename
str
File to parse.
- format
str
File format specifier.
- time_column
str
, optional The name of the time column.
- time_format
str
, optional The time format for the time column.
- time_scale
str
, optional The time scale for the time column.
- *args
tuple
, optional Positional arguments passed through to the data reader.
- **kwargs
dict
, optional Keyword arguments passed through to the data reader.
- filename
- Returns:
- out
astropy.timeseries.sampled.TimeSeries
TimeSeries corresponding to file contents.
- out
Notes
The available built-in formats are:
Format
Read
Write
Auto-identify
kepler.fits
Yes
No
No
tess.fits
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
- 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
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.
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
- colname
- remove_row(index)#
Remove a row from the table.
- Parameters:
- index
int
Index of row to remove
- index
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.
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 by setting the
name
attribute of theinfo
property of the column:table[name].info.name = new_name
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
- rename_columns(names, new_names)#
Rename multiple columns.
- Parameters:
Examples
Create a table with three columns ‘a’, ‘b’, ‘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 columns ‘a’ to ‘aa’ and ‘b’ to ‘bb’:
>>> names = ('a','b') >>> new_names = ('aa','bb') >>> t.rename_columns(names, new_names) >>> print(t) aa bb c --- --- --- 1 3 5 2 4 6
- replace_column(name, col, copy=True)#
Replace column
name
with the newcol
object.The behavior of
copy
for Column objects is: - copy=True: new class instance with a copy of data and deep copy of meta - copy=False: new class instance with same data and a key-only copy of metaFor mixin columns: - copy=True: new class instance with copy of data and deep copy of meta - copy=False: original instance (no copy at all)
- Parameters:
See also
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
- round(decimals=0)#
Round numeric columns in-place to the specified number of decimals. Non-numeric columns will be ignored.
- Parameters:
- decimals: int, dict
Number of decimals to round the columns to. If a dict is given, the columns will be rounded to the number specified as the value. If a certain column is not in the dict given, it will remain the same.
Examples
Create three columns with different types:
>>> t = Table([[1, 4, 5], [-25.55, 12.123, 85], ... ['a', 'b', 'c']], names=('a', 'b', 'c')) >>> print(t) a b c --- ------ --- 1 -25.55 a 4 12.123 b 5 85.0 c
Round them all to 0:
>>> t.round(0) >>> print(t) a b c --- ----- --- 1 -26.0 a 4 12.0 b 5 85.0 c
Round column ‘a’ to -1 decimal:
>>> t.round({'a':-1}) >>> print(t) a b c --- ----- --- 0 -26.0 a 0 12.0 b 0 85.0 c
- setdefault(name, default)#
Ensure a column named
name
exists.If
name
is already present thendefault
is ignored. Otherwisedefault
can be any data object which is acceptable as aTable
column object or can be converted. This includes mixin columns and scalar or length=1 objects which get broadcast to match the table length.- Parameters:
- Returns:
Column
,MaskedColumn
or mixin-column typeThe column named
name
if it is present already, or the validateddefault
converted to a column otherwise.
- Raises:
TypeError
If the table is empty and
default
is a scalar object.
Examples
Start with a simple table:
>>> t0 = Table({"a": ["Ham", "Spam"]}) >>> t0 <Table length=2> a str4 ---- Ham Spam
Trying to add a column that already exists does not modify it:
>>> t0.setdefault("a", ["Breakfast"]) <Column name='a' dtype='str4' length=2> Ham Spam >>> t0 <Table length=2> a str4 ---- Ham Spam
But if the column does not exist it will be created with the default value:
>>> t0.setdefault("approved", False) <Column name='approved' dtype='bool' length=2> False False >>> t0 <Table length=2> a approved str4 bool ---- -------- Ham False Spam False
- show_in_browser(max_lines=5000, jsviewer=False, browser='default', jskwargs={'use_local_files': True}, tableid=None, table_class='display compact', css=None, show_row_index='idx')#
Deprecated since version 6.1: We are planning on deprecating show_in_browser in the future. If you are actively using this method, please let us know at astropy/astropy#16067
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.- jsviewerbool
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
orNone
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
orNone
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 https://www.datatables.net/manual/styling/classes
- css
str
A valid CSS string declaring the formatting for the table. Defaults to
astropy.table.jsviewer.DEFAULT_CSS
.- show_row_index
str
orFalse
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”.
- max_lines
- show_in_notebook(tableid=None, css=None, display_length=50, table_class='astropy-default', show_row_index='idx')#
Deprecated since version 6.1: show_in_notebook() is deprecated as of 6.1 and to create interactive tables it is recommended to use dedicated tools like: - bloomberg/ipydatagrid - https://docs.bokeh.org/en/latest/docs/user_guide/interaction/widgets.html#datatable - https://dash.plotly.com/datatable
Render the table in HTML and show it in the IPython notebook.
- Parameters:
- tableid
str
orNone
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
orNone
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
str
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
orFalse
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”.
- tableid
Notes
Currently, unlike
show_in_browser
(withjsviewer=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, *, kind=None, reverse=False)#
Sort the table according to one or more keys. This operates on the existing table and does not return a new table.
- Parameters:
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
Sorting according to standard sorting rules, first ‘firstname’ then ‘tel’, in reverse order:
>>> t.sort(['firstname', 'tel'], reverse=True) >>> print(t) firstname name tel --------- ------- --- Max Miller 12 John Jackson 18 Jo Miller 15
- to_pandas()[source]#
Convert this
TimeSeries
to aDataFrame
with aDatetimeIndex
index.- Returns:
- dataframe
pandas.DataFrame
A pandas
pandas.DataFrame
instance
- dataframe
- update(other, copy=True)#
Perform a dictionary-style update and merge metadata.
The argument
other
must be aTable
, or something that can be used to initialize a table. Columns from (possibly converted)other
are added to this table. In case of matching column names the column from this table is replaced with the one fromother
. Ifother
is aTable
instance then|=
is available as alternate syntax for in-place update and|
can be used merge data to a new table.- Parameters:
- otherastropy:table-like
Data to update this table with.
- copybool
Whether the updated columns should be copies of or references to the originals.
See also
Examples
Update a table with another table:
>>> t1 = Table({'a': ['foo', 'bar'], 'b': [0., 0.]}, meta={'i': 0}) >>> t2 = Table({'b': [1., 2.], 'c': [7., 11.]}, meta={'n': 2}) >>> t1.update(t2) >>> t1 <Table length=2> a b c str3 float64 float64 ---- ------- ------- foo 1.0 7.0 bar 2.0 11.0 >>> t1.meta {'i': 0, 'n': 2}
Update a table with a dictionary:
>>> t = Table({'a': ['foo', 'bar'], 'b': [0., 0.]}) >>> t.update({'b': [1., 2.]}) >>> t <Table length=2> a b str3 float64 ---- ------- foo 1.0 bar 2.0
- values()#
- values_equal(other)#
Element-wise comparison of table with another table, list, or scalar.
Returns a
Table
with the same columns containing boolean values showing result of comparison.- Parameters:
- otherastropy:table-like
object
orlist
or scalar Object to compare with table
- otherastropy:table-like
Examples
Compare one Table with other:
>>> t1 = Table([[1, 2], [4, 5], [-7, 8]], names=('a', 'b', 'c')) >>> t2 = Table([[1, 2], [-4, 5], [7, 8]], names=('a', 'b', 'c')) >>> t1.values_equal(t2) <Table length=2> a b c bool bool bool ---- ----- ----- True False False True True True