larray.Array¶
-
class
larray.
Array
(data, axes=None, title=None, meta=None, dtype=None)[source]¶ An Array object represents a multidimensional, homogeneous array of fixed-size items with labeled axes.
The function
asarray()
can be used to convert a NumPy array or Pandas DataFrame into an Array.- Parameters
- datascalar, tuple, list or NumPy ndarray
Input data.
- axescollection (tuple, list or AxisCollection) of axes (int, str or Axis), optional
Axes.
- titlestr, optional
Deprecated. See ‘meta’ below.
- metalist of pairs or dict or OrderedDict or Metadata, optional
Metadata (title, description, author, creation_date, …) associated with the array. Keys must be strings. Values must be of type string, int, float, date, time or datetime.
- dtypetype, optional
Datatype for the array. Defaults to None (inferred from the data).
Warning
Metadata is not kept when actions or methods are applied on an array except for operations modifying the object in-place, such as: pop[age < 10] = 0. Do not add metadata to an array if you know you will apply actions or methods on it before dumping it.
See also
sequence
Create an Array by sequentially applying modifications to the array along axis.
ndtest
Create a test Array with increasing elements.
zeros
Create an Array, each element of which is zero.
ones
Create an Array, each element of which is 1.
full
Create an Array filled with a given value.
empty
Create an Array, but leave its allocated memory unchanged (i.e., it contains “garbage”).
Examples
>>> age = Axis([10, 11, 12], 'age') >>> sex = Axis('sex=M,F') >>> time = Axis([2007, 2008, 2009], 'time') >>> axes = [age, sex, time] >>> data = np.zeros((len(axes), len(sex), len(time)))
>>> Array(data, axes) age sex\time 2007 2008 2009 10 M 0.0 0.0 0.0 10 F 0.0 0.0 0.0 11 M 0.0 0.0 0.0 11 F 0.0 0.0 0.0 12 M 0.0 0.0 0.0 12 F 0.0 0.0 0.0 >>> # with metadata (Python <= 3.5) >>> arr = Array(data, axes, meta=[('title', 'my title'), ('author', 'John Smith')]) >>> # with metadata (Python 3.6+) >>> arr = Array(data, axes, meta=Metadata(title='my title', author='John Smith'))
Array creation functions
>>> full(axes, 10.0) age sex\time 2007 2008 2009 10 M 10.0 10.0 10.0 10 F 10.0 10.0 10.0 11 M 10.0 10.0 10.0 11 F 10.0 10.0 10.0 12 M 10.0 10.0 10.0 12 F 10.0 10.0 10.0 >>> arr = empty(axes) >>> arr['F'] = 1.0 >>> arr['M'] = -1.0 >>> arr age sex\time 2007 2008 2009 10 M -1.0 -1.0 -1.0 10 F 1.0 1.0 1.0 11 M -1.0 -1.0 -1.0 11 F 1.0 1.0 1.0 12 M -1.0 -1.0 -1.0 12 F 1.0 1.0 1.0 >>> bysex = sequence(sex, initial=-1, inc=2) >>> bysex sex M F -1 1 >>> sequence(age, initial=10, inc=bysex) sex\age 10 11 12 M 10 9 8 F 10 11 12
- Attributes
- dataNumPy ndarray
Data.
- axesAxisCollection
Axes.
meta
MetadataReturns metadata of the array.
-
__init__
(self, data, axes=None, title=None, meta=None, dtype=None)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
(self, data[, axes, title, meta, dtype])Initialize self.
align
(self, other[, join, fill_value, axes])Align two arrays on their axes with the specified join method.
all
(*axes_and_groups[, out, skipna, keepaxes])Test whether all selected elements evaluate to True.
all_by
(*axes_and_groups[, out, skipna, keepaxes])Test whether all selected elements evaluate to True.
any
(*axes_and_groups[, out, skipna, keepaxes])Test whether any selected elements evaluate to True.
any_by
(*axes_and_groups[, out, skipna, keepaxes])Test whether any selected elements evaluate to True.
append
(self, axis, value[, label])Adds an array to self along an axis.
apply
(self, transform, \*args, \*\*kwargs)Apply a transformation function to array elements.
apply_map
(self, mapping[, dtype])Apply a transformation mapping to array elements.
argmax
(\*args, \*\*kwargs)argmin
(\*args, \*\*kwargs)argsort
(\*args, \*\*kwargs)as_table
(self[, maxlines, edgeitems, light, …])Deprecated.
astype
(dtype[, order, casting, subok, copy])Copy of the array, cast to a specified type.
broadcast_with
(self, target)Returns an array that is (NumPy) broadcastable with target.
clip
(self[, minval, maxval, out])Clip (limit) the values in an array.
combine_axes
(self[, axes, sep, wildcard])Combine several axes into one.
compact
(self)Detects and removes “useless” axes (ie axes for which values are constant over the whole axis)
copy
(self)Returns a copy of the array.
cumprod
(self[, axis])Returns the cumulative product of array elements.
cumsum
(self[, axis])Returns the cumulative sum of array elements along an axis.
describe
(self, \*args, \*\*kwargs)Descriptive summary statistics, excluding NaN values.
describe_by
(self, \*args, \*\*kwargs)Descriptive summary statistics, excluding NaN values, along axes or for groups.
diff
(self[, axis, d, n, label])Calculates the n-th order discrete difference along a given axis.
divnot0
(self, other)Divides array by other, but returns 0.0 where other is 0.
drop
(self[, labels])Return array without some labels or indices along an axis.
drop_labels
(\*args, \*\*kwargs)dump
(self[, header, wide, value_name, …])Dump array as a 2D nested list.
eq
(self, other[, rtol, atol, nans_equal])Compares self with another array element-wise and returns an array of booleans.
equals
(self, other[, rtol, atol, …])Compares self with another array and returns True if they have the same axes and elements, False otherwise.
expand
(self[, target_axes, out, readonly])Expands array to target_axes.
extend
(self, axis, other)Adds an array to self along an axis.
filter
(self[, collapse])Filters the array along the axes given as keyword arguments.
growth_rate
(self[, axis, d, label])Calculates the growth along a given axis.
ignore_labels
(self[, axes])Ignore labels from axes (replace those axes by “wildcard” axes).
indexofmax
(self[, axis])Returns indices of the maximum values along a given axis.
indexofmin
(self[, axis])Returns indices of the minimum values along a given axis.
indicesofsorted
(self[, axis, ascending, kind])Returns the indices that would sort this array.
insert
(self, value[, before, after, pos, …])Inserts value in array along an axis.
isin
(self, test_values[, assume_unique, invert])Computes whether each element of this array is in test_values.
items
(self[, axes, ascending])Returns a (label, value) view of the array along axes.
keys
(self[, axes, ascending])Returns a view on the array labels along axes.
labelofmax
(self[, axis])Returns labels of the maximum values along a given axis.
labelofmin
(self[, axis])Returns labels of the minimum values along a given axis.
labelsofsorted
(self[, axis, ascending, kind])Returns the labels that would sort this array.
max
(*axes_and_groups[, out, skipna, keepaxes])Get maximum of array elements along given axes/groups.
max_by
(*axes_and_groups[, out, skipna, keepaxes])Get maximum of array elements for the given axes/groups.
mean
(*axes_and_groups[, dtype, out, skipna, …])Computes the arithmetic mean.
mean_by
(*axes_and_groups[, dtype, out, …])Computes the arithmetic mean.
median
(*axes_and_groups[, out, skipna, keepaxes])Computes the arithmetic median.
median_by
(*axes_and_groups[, out, skipna, …])Computes the arithmetic median.
min
(*axes_and_groups[, out, skipna, keepaxes])Get minimum of array elements along given axes/groups.
min_by
(*axes_and_groups[, out, skipna, keepaxes])Get minimum of array elements for the given axes/groups.
nonzero
(self)Returns the indices of the elements that are non-zero.
percent
(self, \*axes)Returns an array with values given as percent of the total of all values along given axes.
percentile
(q, *axes_and_groups[, out, …])Computes the qth percentile of the data along the specified axis.
percentile_by
(q, *axes_and_groups[, out, …])Computes the qth percentile of the data for the specified axis.
posargmax
(\*args, \*\*kwargs)posargmin
(\*args, \*\*kwargs)posargsort
(\*args, \*\*kwargs)prepend
(self, axis, value[, label])Adds an array before self along an axis.
prod
(*axes_and_groups[, dtype, out, skipna, …])Computes the product of array elements along given axes/groups.
prod_by
(*axes_and_groups[, dtype, out, …])Computes the product of array elements for the given axes/groups.
ptp
(*axes_and_groups[, out])Returns the range of values (maximum - minimum).
ratio
(self, \*axes)Returns an array with all values divided by the sum of values along given axes.
rationot0
(self, \*axes)Returns an Array with values array / array.sum(axes) where the sum is not 0, 0 otherwise.
reindex
(self[, axes_to_reindex, new_axis, …])Reorder and/or add new labels in axes.
rename
(self[, renames, to, inplace])Renames axes of the array.
reshape
(self, target_axes)Given a list of new axes, changes the shape of the array.
reshape_like
(self, target)Same as reshape but with an array as input.
reverse
(self[, axes])Reverse axes of an array
roll
(self[, axis, n])Rolls the cells of the array n-times to the right along axis.
set
(self, value, \*\*kwargs)Sets a subset of array to value.
set_axes
(self[, axes_to_replace, new_axis, …])Replace one, several or all axes of the array.
set_labels
(self[, axis, labels, inplace])Replaces the labels of one or several axes of the array.
shift
(self, axis[, n])Shifts the cells of the array n-times to the right along axis.
sort_axes
(self[, axes, ascending])Sorts axes of the array.
sort_axis
(\*args, \*\*kwargs)sort_values
(self[, key, axis, ascending])Sorts values of the array.
split_axes
(self[, axes, sep, names, regex, …])Split axes and returns a new array
split_axis
(\*args, \*\*kwargs)std
(*axes_and_groups[, dtype, ddof, out, …])Computes the sample standard deviation.
std_by
(*axes_and_groups[, dtype, ddof, out, …])Computes the sample standard deviation.
sum
(*axes_and_groups[, dtype, out, skipna, …])Computes the sum of array elements along given axes/groups.
sum_by
(*axes_and_groups[, dtype, out, …])Computes the sum of array elements for the given axes/groups.
to_clipboard
(self, \*args, \*\*kwargs)Sends the content of the array to clipboard.
to_csv
(self, filepath[, sep, na_rep, wide, …])Writes array to a csv file.
to_excel
(self[, filepath, sheet, position, …])Writes array in the specified sheet of specified excel workbook.
to_frame
(self[, fold_last_axis_name, dropna])Converts an Array into a Pandas DataFrame.
to_hdf
(self, filepath, key)Writes array to a HDF file.
to_series
(self[, name, dropna])Converts an Array into a Pandas Series.
to_stata
(self, filepath_or_buffer, \*\*kwargs)Writes array to a Stata .dta file.
transpose
(self, \*args)Reorder axes.
unique
(self[, axes, sort, sep])Returns unique values (optionally along axes)
values
(self[, axes, ascending])Returns a view on the values of the array along axes.
var
(*axes_and_groups[, dtype, ddof, out, …])Computes the unbiased variance.
var_by
(*axes_and_groups[, dtype, ddof, out, …])Computes the unbiased variance.
with_axes
(\*args, \*\*kwargs)with_total
(*args[, op, label])Add aggregated values (sum by default) along each axis.
Attributes
T
Reorder axes.
axes
data
df
Converts an Array into a Pandas DataFrame.
Returns the type of the data of the array.
Allows selection of a subset using indices of labels.
Access the array by index as if it was flat (one dimensional) and all its axes were combined.
Describes an Array (metadata + shape and labels for each axis).
Allows selection of arbitrary items in the array based on their N-dimensional index.
item
Returns the memory consumed by the array in human readable form.
meta
Returns metadata of the array.
Returns the number of bytes used to store the array in memory.
Returns the number of dimensions of the array.
Plots the data of the array into a graph (window pop-up).
Allows selection of arbitrary items in the array based on their N-dimensional label index.
series
Converts an Array into a Pandas Series.
Returns the shape of the array as a tuple.
Returns the number of elements in array.
title