78 lines
5.1 KiB
Plaintext
78 lines
5.1 KiB
Plaintext
---
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title: plot_distribution (latest version)
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description: API reference for qiskit.visualization.plot_distribution in the latest version of qiskit
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in_page_toc_min_heading_level: 1
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python_api_type: function
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python_api_name: qiskit.visualization.plot_distribution
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---
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<span id="qiskit-visualization-plot-distribution" />
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# qiskit.visualization.plot\_distribution
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<Function id="qiskit.visualization.plot_distribution" isDedicatedPage={true} github="https://github.com/Qiskit/qiskit/tree/stable/1.2/qiskit/visualization/counts_visualization.py#L165-L258" signature="qiskit.visualization.plot_distribution(data, figsize=(7, 5), color=None, number_to_keep=None, sort='asc', target_string=None, legend=None, bar_labels=True, title=None, ax=None, filename=None)">
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Plot a distribution from input sampled data.
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**Parameters**
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* **data** ([*list*](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.13)") *or*[*dict*](https://docs.python.org/3/library/stdtypes.html#dict "(in Python v3.13)")) – This is either a list of dictionaries or a single dict containing the values to represent (ex \{‘001’: 130})
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* **figsize** ([*tuple*](https://docs.python.org/3/library/stdtypes.html#tuple "(in Python v3.13)")) – Figure size in inches.
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* **color** ([*list*](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.13)") *or*[*str*](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.13)")) – String or list of strings for distribution bar colors.
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* **number\_to\_keep** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of terms to plot per dataset. The rest is made into a single bar called ‘rest’. If multiple datasets are given, the `number_to_keep` applies to each dataset individually, which may result in more bars than `number_to_keep + 1`. The `number_to_keep` applies to the total values, rather than the x-axis sort.
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* **sort** (*string*) – Could be ‘asc’, ‘desc’, ‘hamming’, ‘value’, or ‘value\_desc’. If set to ‘value’ or ‘value\_desc’ the x axis will be sorted by the maximum probability for each bitstring. Defaults to ‘asc’.
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* **target\_string** ([*str*](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.13)")) – Target string if ‘sort’ is a distance measure.
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* **legend** ([*list*](https://docs.python.org/3/library/stdtypes.html#list "(in Python v3.13)")) – A list of strings to use for labels of the data. The number of entries must match the length of data (if data is a list or 1 if it’s a dict)
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* **bar\_labels** ([*bool*](https://docs.python.org/3/library/functions.html#bool "(in Python v3.13)")) – Label each bar in histogram with probability value.
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* **title** ([*str*](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.13)")) – A string to use for the plot title
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* **ax** ([*matplotlib.axes.Axes*](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes "(in Matplotlib v3.9.2)")) – An optional Axes object to be used for the visualization output. If none is specified a new matplotlib Figure will be created and used. Additionally, if specified there will be no returned Figure since it is redundant.
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* **filename** ([*str*](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.13)")) – file path to save image to.
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**Returns**
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A figure for the rendered distribution, if the `ax` kwarg is not set.
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**Return type**
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matplotlib.Figure
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**Raises**
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* [**MissingOptionalLibraryError**](exceptions#qiskit.exceptions.MissingOptionalLibraryError "qiskit.exceptions.MissingOptionalLibraryError") – Matplotlib not available.
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* [**VisualizationError**](visualization#qiskit.visualization.VisualizationError "qiskit.visualization.VisualizationError") – When legend is provided and the length doesn’t match the input data.
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**Examples**
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```python
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# Plot two counts in the same figure with legends and colors specified.
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from qiskit.visualization import plot_distribution
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counts1 = {'00': 525, '11': 499}
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counts2 = {'00': 511, '11': 514}
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legend = ['First execution', 'Second execution']
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plot_distribution([counts1, counts2], legend=legend, color=['crimson','midnightblue'],
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title="New Distribution")
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# You can sort the bitstrings using different methods.
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counts = {'001': 596, '011': 211, '010': 50, '000': 117, '101': 33, '111': 8,
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'100': 6, '110': 3}
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# Sort by the counts in descending order
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dist1 = plot_distribution(counts, sort='value_desc')
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# Sort by the hamming distance (the number of bit flips to change from
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# one bitstring to the other) from a target string.
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dist2 = plot_distribution(counts, sort='hamming', target_string='001')
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```
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</Function>
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