# Uniform

How to sample numbers from any uniform distribution on the real line.

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In [1]:

```
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
```

#### Uniform¶

Unlike `np.random.random()`

where you can sample a number between a fixed interval of [0, 1), `np.random.uniform()`

allows you to set your own `low`

and `high`

bounds to your interval and draw uniformly from that. Also like `np.random.random()`

, there is a `size`

parameter for sampling several times from the uniform distribution.

In [2]:

```
import plotly.plotly as py
import plotly.graph_objs as go
num_of_points = 150
uniform_array_1 = np.random.uniform(0, 1, num_of_points)
uniform_array_2 = np.random.uniform(2, 4, num_of_points)
uniform_array_3 = np.random.uniform(6, 10, num_of_points)
trace1 = go.Scatter(
x=[j for j in range(num_of_points)],
y=uniform_array_1,
mode='markers',
marker = dict(
size=14,
color=uniform_array_1,
colorscale='Reds'
),
name='[0, 1]'
)
trace2 = go.Scatter(
x=[j for j in range(num_of_points)],
y=uniform_array_2,
mode='markers',
marker = dict(
size=13,
color=uniform_array_2,
colorscale='Blues'
),
name='[2, 4]'
)
trace3 = go.Scatter(
x=[j for j in range(num_of_points)],
y=uniform_array_3,
mode='markers',
marker = dict(
size=12,
color=uniform_array_3,
colorscale='Greens'
),
name='[6, 10]'
)
py.iplot([trace1, trace2, trace3], filename='numpy-uniform')
```

Out[2]:

In [4]:

```
help(np.random.uniform)
```