> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Histogram
export const GitHubLink = ({url}) =>
GitHub source
;
## class `Histogram`
W\&B class for histograms.
This object works just like numpy's histogram function [https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html](https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html)
**Attributes:**
* `bins` (\[float]): Edges of bins
* `histogram` (\[int]): Number of elements falling in each bin.
### method `Histogram.__init__`
```python theme={null}
__init__(
sequence: 'Sequence | None' = None,
np_histogram: 'NumpyHistogram | None' = None,
num_bins: 'int' = 64
) → None
```
Initialize a Histogram object.
**Args:**
sequence: Input data for histogram. np\_histogram: Alternative input of a precomputed histogram. num\_bins: Number of bins for the histogram. The default number of bins is 64. The maximum number of bins is 512.
**Examples:**
Generate histogram from a sequence.
```python theme={null}
import wandb
wandb.Histogram([1, 2, 3])
```
Efficiently initialize from np.histogram.
```python theme={null}
import numpy as np
import wandb
hist = np.histogram(data)
wandb.Histogram(np_histogram=hist)
```
***