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import itertools |
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import numpy as np |
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from typing import List, Union |
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import plotly.graph_objects as go |
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from plotly.subplots import make_subplots |
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def visualize_barchart(topic_model, |
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topics: List[int] = None, |
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top_n_topics: int = 8, |
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n_words: int = 5, |
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custom_labels: Union[bool, str] = False, |
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title: str = "<b>Topic Word Scores</b>", |
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width: int = 250, |
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height: int = 250) -> go.Figure: |
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""" Visualize a barchart of selected topics |
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Arguments: |
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topic_model: A fitted BERTopic instance. |
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topics: A selection of topics to visualize. |
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top_n_topics: Only select the top n most frequent topics. |
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n_words: Number of words to show in a topic |
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custom_labels: If bool, whether to use custom topic labels that were defined using |
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`topic_model.set_topic_labels`. |
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If `str`, it uses labels from other aspects, e.g., "Aspect1". |
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title: Title of the plot. |
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width: The width of each figure. |
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height: The height of each figure. |
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Returns: |
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fig: A plotly figure |
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Examples: |
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To visualize the barchart of selected topics |
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simply run: |
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```python |
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topic_model.visualize_barchart() |
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``` |
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Or if you want to save the resulting figure: |
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```python |
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fig = topic_model.visualize_barchart() |
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fig.write_html("path/to/file.html") |
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``` |
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<iframe src="../../getting_started/visualization/bar_chart.html" |
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style="width:1100px; height: 660px; border: 0px;""></iframe> |
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""" |
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colors = itertools.cycle(["#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#009E73", "#F0E442"]) |
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freq_df = topic_model.get_topic_freq() |
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freq_df = freq_df.loc[freq_df.Topic != -1, :] |
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if topics is not None: |
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topics = list(topics) |
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elif top_n_topics is not None: |
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topics = sorted(freq_df.Topic.to_list()[:top_n_topics]) |
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else: |
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topics = sorted(freq_df.Topic.to_list()[0:6]) |
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if isinstance(custom_labels, str): |
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subplot_titles = [[[str(topic), None]] + topic_model.topic_aspects_[custom_labels][topic] for topic in topics] |
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subplot_titles = ["_".join([label[0] for label in labels[:4]]) for labels in subplot_titles] |
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subplot_titles = [label if len(label) < 30 else label[:27] + "..." for label in subplot_titles] |
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elif topic_model.custom_labels_ is not None and custom_labels: |
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subplot_titles = [topic_model.custom_labels_[topic + topic_model._outliers] for topic in topics] |
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else: |
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subplot_titles = [f"Topic {topic}" for topic in topics] |
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columns = 4 |
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rows = int(np.ceil(len(topics) / columns)) |
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fig = make_subplots(rows=rows, |
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cols=columns, |
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shared_xaxes=False, |
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horizontal_spacing=.1, |
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vertical_spacing=.4 / rows if rows > 1 else 0, |
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subplot_titles=subplot_titles) |
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row = 1 |
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column = 1 |
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for topic in topics: |
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words = [word + " " for word, _ in topic_model.get_topic(topic)][:n_words][::-1] |
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scores = [score for _, score in topic_model.get_topic(topic)][:n_words][::-1] |
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fig.add_trace( |
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go.Bar(x=scores, |
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y=words, |
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orientation='h', |
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marker_color=next(colors)), |
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row=row, col=column) |
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if column == columns: |
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column = 1 |
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row += 1 |
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else: |
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column += 1 |
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fig.update_layout( |
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template="plotly_white", |
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showlegend=False, |
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title={ |
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'text': f"{title}", |
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'x': .5, |
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'xanchor': 'center', |
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'yanchor': 'top', |
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'font': dict( |
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size=22, |
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color="Black") |
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}, |
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width=width*4, |
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height=height*rows if rows > 1 else height * 1.3, |
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hoverlabel=dict( |
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bgcolor="white", |
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font_size=16, |
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font_family="Rockwell" |
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), |
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) |
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fig.update_xaxes(showgrid=True) |
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fig.update_yaxes(showgrid=True) |
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return fig |
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