77 lines
4.0 KiB
Plaintext
77 lines
4.0 KiB
Plaintext
---
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title: plot_histogram
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description: API reference for qiskit.visualization.plot_histogram
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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_histogram
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---
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# qiskit.visualization.plot\_histogram
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<Function id="qiskit.visualization.plot_histogram" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.23/qiskit/visualization/counts_visualization.py" signature="plot_histogram(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 histogram of input counts data.
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**Parameters**
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* **data** (*list or dict*) – 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*) – Figure size in inches.
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* **color** (*list or str*) – String or list of strings for histogram bar colors.
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* **number\_to\_keep** (*int*) – 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 number of counts for each bitstring. Defaults to ‘asc’.
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* **target\_string** (*str*) – Target string if ‘sort’ is a distance measure.
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* **legend** (*list*) – 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*) – Label each bar in histogram with counts value.
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* **title** (*str*) – A string to use for the plot title
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* **ax** (*matplotlib.axes.Axes*) – 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*) – file path to save image to.
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**Returns**
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A figure for the rendered histogram, 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** – Matplotlib not available.
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* [**VisualizationError**](qiskit.visualization.VisualizationError "qiskit.visualization.VisualizationError") – When legend is provided and the length doesn’t match the input data.
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* [**VisualizationError**](qiskit.visualization.VisualizationError "qiskit.visualization.VisualizationError") – Input must be Counts or a dict
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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_histogram
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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_histogram([counts1, counts2], legend=legend, color=['crimson','midnightblue'],
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title="New Histogram")
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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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hist1 = plot_histogram(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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hist2 = plot_histogram(counts, sort='hamming', target_string='001')
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```
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</Function>
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