import solara import numpy as np import plotly.express as px from utils import selected_template @solara.component def Histograms(): with solara.Column(gap="20px", align = "stretch") as main: solara.Markdown(f"#HISTOGRAMS") # Plot histogram based on rolling 2 dice dice_1 = np.random.randint(1,7,5000) dice_2 = np.random.randint(1,7,5000) dice_sum = dice_1 + dice_2 # bins represent the number of bars to make # Can define x label, color, title # marginal creates another plot (violin, box, rug) fig1 = px.histogram(dice_sum, nbins=11, labels={'value':'Dice Roll'}, title='5000 Dice Roll Histogram', marginal='violin', color_discrete_sequence=['green']) fig1.update_layout( xaxis_title_text='Dice Roll', yaxis_title_text='Dice Sum', bargap=0.2, showlegend=False, template=selected_template.value ) solara.Markdown(f"#### Plot histogram based on rolling 2 dice ") solara.Markdown(""" ```python dice_1 = np.random.randint(1,7,5000) dice_2 = np.random.randint(1,7,5000) dice_sum = dice_1 + dice_2 # bins represent the number of bars to make # Can define x label, color, title # marginal creates another plot (violin, box, rug) fig1 = px.histogram(dice_sum, nbins=11, labels={'value':'Dice Roll'}, title='5000 Dice Roll Histogram', marginal='violin', color_discrete_sequence=['green']) fig1.update_layout( xaxis_title_text='Dice Roll', yaxis_title_text='Dice Sum', bargap=0.2, showlegend=False ) ``` """ ) solara.FigurePlotly(fig1) # Stack histograms based on different column data df_tips = px.data.tips() fig2= px.histogram(df_tips, x="total_bill", color="sex",template=selected_template.value) solara.Markdown(f"####Stack histograms based on different column data") solara.Markdown(""" ```python df_tips = px.data.tips() px.histogram(df_tips, x="total_bill", color="sex") ``` """ ) solara.FigurePlotly(fig2) return main