20200316_dash_nlp_dash_snippet.py

dbc.Row([
    dbc.Col(['Choose a t-SNE perplexity value:'], md=6),
    dbc.Col([
        dcc.Dropdown(
            id='bigrams-perplex-dropdown',
            options=[{'label': str(i), 'value': i} for i in range(3, 7)],
            value=3
        )], md=3)
]),
dcc.Graph(id="bigrams-scatter"),

...

@app.callback(
    Output("bigrams-scatter", "figure"),
    [Input("bigrams-perplex-dropdown", "value")],
)
def populate_bigram_scatter(perplexity):
    X_embedded = TSNE(n_components=2, perplexity=perplexity).fit_transform(vects_df)

    embed_df['tsne_1'] = X_embedded[:, 0]
    embed_df['tsne_2'] = X_embedded[:, 1]
    fig = px.scatter(embed_df, x='tsne_1', y='tsne_2', hover_name='bigram', text='bigram', size='count', color='words', size_max=45
                     , template='plotly_white', title='Bigram similarity and frequency', labels={'words': 'Avg. Length<BR>(words)'}
                     , color_continuous_scale=px.colors.sequential.Sunsetdark)
    fig.update_traces(marker=dict(line=dict(width=1, color='Gray')))
    fig.update_xaxes(visible=False)
    fig.update_yaxes(visible=False)
    return fig