larry methods

The larry methods can be divided into the following broad categories:

Below you’ll find the methods in each category along with examples. All of the examples assume that you have already imported larry:

>>> from la import larry

The reference guide for the larry functions, as opposed to methods, can be found in larry functions.

Creation

The creation methods allow you to create larrys.






Unary

The unary functions (such as log, sqrt, sign) operate on a single larry and do not change its shape or ordering.















Binary methods

The binary methods (such as +, -, / and *) combine a larry with a scalar, Numpy array, or another larry. More general binary functions, that give you control of the join method and the fill method can be found in Binary functions.







Reduce

The reduce methods (such as sum and std) aggregate along an axis or axes thereby reducing the dimension of the larry.













Comparison

The comparison methods, such as ==, >, and !=, perform an element-by-element comparison and return a bool larry. For example:

>>> y1 = larry([1, 2, 3, 4])
>>> y2 = larry([1, 9, 3, 9])
>>> y1 == y2
label_0
    0
    1
    2
    3
x
array([ True, False,  True, False], dtype=bool)

and

>>> from la import larry
>>> y1 = larry([1, 2], [['a', 'b']])
>>> y2 = larry([1, 2], [['b', 'c']])
>>> y1 == y2
label_0
    b
x
array([False], dtype=bool)

A larry can be compared with a scalar, NumPy array, list, tuple, and another larry.

Warning

Do not compare a NumPy array on the left-hand side with a larry on the right-hand side. You will get unexpected results. To compare a larry to a NumPy array, put the array on the right-hand side.







Get and set

The get methods return subsets of a larry through indexing and the set methods assign values to a subset of a larry.














Label

The label methods allow you to get information (and change) the labels of a larry.





Moving window statistics

Moving window statistics along the specified axis of a larry.










Calculation

The calculation methods transform the larry.






Group

The group methods allow you to calculate the group mean (or median or ranking) along axis=0 of a larry. For example, let’s calculate the group mean of y where group 1 is (‘e’, ‘a’), group 2 is (‘d’, ‘c’), and group 3 is (‘b’):

>>> from la import larry
>>> y  = larry([[1], [2], [3], [4], [5]], [['a', 'b', 'c', 'd', 'e'], [0]])
>>> group = larry([1, 1, 2, 2, 3], [['e', 'a', 'd', 'c', 'b']])

>>> y.group_mean(group)
label_0
    a
    b
    c
    d
    e
label_1
    0
x
array([[ 3. ],
       [ 2. ],
       [ 3.5],
       [ 3.5],
       [ 3. ]])



Alignment

There are several alignment methods. See also the align function.








Shuffle

The data and the labels of larrys can be randomly shuffled in-place.



Missing data

NaNs are treated as missing data in larry:

>>> import la
>>> y = larry([1.0, la.nan])
>>> y.sum()
1.0

Missing value makers for various dtypes:

dtype missing marker
float NaN
object None
str ‘’
int, bool, etc Not supported





Size, shape, dtype

Here are the methods that tell you about the size, shape, and dtype of larry. Some of the methods (T, flatten, unflatten) change the shape of the larry.












Conversion

Methods to convert larrys to other formats. For the corresponding ‘from’ methods, see Creation.






Copy

Here are the methods that copy a larry or its components.