Show Sidebar Hide Sidebar

Randint

How to sample numbers from a range of integers uniformly.

New to Plotly?

Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

Imports

This tutorial imports Plotly and Numpy.

In [1]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

Randint

np.random.randint() allows users to pick uniformly from a set of integers [low, low + 1, ..., high].

In [2]:
import plotly.plotly as py
import plotly.graph_objs as go

num_of_points = 200
random_numbers = np.random.randint(0, 10, num_of_points)

trace1 = go.Scatter(
    x=[j for j in range(num_of_points)],
    y=random_numbers,
    mode='markers',
    marker = dict(
        size=7,
        color=random_numbers,
        colorscale='Jet',
        symbol='diamond'
    ),
    name='Numbers sampled from 0 to 9'
)

py.iplot([trace1], filename='numpy-randint')
Out[2]:
In [3]:
help(np.random.randint)
Help on built-in function randint:

randint(...)
    randint(low, high=None, size=None, dtype='l')
    
    Return random integers from `low` (inclusive) to `high` (exclusive).
    
    Return random integers from the "discrete uniform" distribution of
    the specified dtype in the "half-open" interval [`low`, `high`). If
    `high` is None (the default), then results are from [0, `low`).
    
    Parameters
    ----------
    low : int
        Lowest (signed) integer to be drawn from the distribution (unless
        ``high=None``, in which case this parameter is the *highest* such
        integer).
    high : int, optional
        If provided, one above the largest (signed) integer to be drawn
        from the distribution (see above for behavior if ``high=None``).
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  Default is None, in which case a
        single value is returned.
    dtype : dtype, optional
        Desired dtype of the result. All dtypes are determined by their
        name, i.e., 'int64', 'int', etc, so byteorder is not available
        and a specific precision may have different C types depending
        on the platform. The default value is 'np.int'.
    
        .. versionadded:: 1.11.0
    
    Returns
    -------
    out : int or ndarray of ints
        `size`-shaped array of random integers from the appropriate
        distribution, or a single such random int if `size` not provided.
    
    See Also
    --------
    random.random_integers : similar to `randint`, only for the closed
        interval [`low`, `high`], and 1 is the lowest value if `high` is
        omitted. In particular, this other one is the one to use to generate
        uniformly distributed discrete non-integers.
    
    Examples
    --------
    >>> np.random.randint(2, size=10)
    array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])
    >>> np.random.randint(1, size=10)
    array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
    
    Generate a 2 x 4 array of ints between 0 and 4, inclusive:
    
    >>> np.random.randint(5, size=(2, 4))
    array([[4, 0, 2, 1],
           [3, 2, 2, 0]])

Still need help?
Contact Us

For guaranteed 24 hour response turnarounds, upgrade to a Developer Support Plan.