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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
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