Search code examples
pythonplotplotlyvisualization

Plotly dropdown is not changing the plot as desired

I am trying to plot the line graph using plotly. I need to select the grade and then plot two liones of min and max on the plot for the selected grade.


import plotly.express as px
import pandas as pd
import ipywidgets as widgets
from IPython.display import display

# Sample data
data = {
    'index': [1, 2, 3, 4, 5],
    'Grade': ['STEEL', 'IRON', 'CU', 'ALU', 'BRO'],
    'SIZE': [1, 2, 3, 4, 5],
    'min': [10, 20, 15, 25, 30],
    'max': [30, 40, 35, 45, 50]
}

df = pd.DataFrame(data)

# Create an initial plot for min and max for all Grades
fig = px.line(df, x='index', y=['min', 'max'], line_shape='linear',
              labels={'value': 'Values'}, title='min and max Plot for All Grades', template='plotly_white')

fig.update_layout(
    xaxis_title='Index',
    yaxis_title='Values',
    legend_title='Grade'
)

# Dropdown widget for selecting Grade
grade_dropdown = widgets.Dropdown(
    options=df['Grade'].unique().tolist(),
    value=df['Grade'].unique()[0],
    description='Select Grade:',
)

# Function to update the plot based on selected Grade
def update_plot(selected_grade):
    filtered_df = df[df['Grade'] == selected_grade]
    fig.update_traces(x=filtered_df['index'], y=[filtered_df['min'], filtered_df['max']])
    fig.update_layout(title=f'min and max Plot for Grade {selected_grade}')

# Dropdown value change event handler
def on_dropdown_change(change):
    update_plot(change['new'])

grade_dropdown.observe(on_dropdown_change, names='value')

# Display the dropdown widget and the initial plot
display(grade_dropdown)
fig.show()

The output is like below

When I change the Grade lets say 'STEEL', it does not change the plot. It stays static. FOr steel, It should show 10 for min and 30 for max only .Can anyone help me with this ?

Solution

  • We can use clear_output from IPython.display to clear the screen. Then we draw the dropdown and the chart again after clearing.

    import plotly.express as px
import pandas as pd
import ipywidgets as widgets
from IPython.display import display, clear_output


# Sample data
data = {
    'index': [1, 2, 3, 4, 5],
    'Grade': ['STEEL', 'IRON', 'CU', 'ALU', 'BRO'],
    'SIZE': [1, 2, 3, 4, 5],
    'min': [10, 20, 15, 25, 30],
    'max': [30, 40, 35, 45, 50]
}

df = pd.DataFrame(data)

# Create an initial plot for min and max for all Grades
fig = px.line(df, x='index', y=['min', 'max'], line_shape='linear',
              labels={'value': 'Values'}, title='min and max Plot for All Grades', template='plotly_white')

fig.update_layout(
    xaxis_title='Index',
    yaxis_title='Values',
    legend_title='Grade'
)

# Dropdown widget for selecting Grade
grade_dropdown = widgets.Dropdown(
    options=df['Grade'].unique().tolist(),
    value=df['Grade'].unique()[0],
    description='Select Grade:',
)

# Function to update the plot based on selected Grade
def update_plot(selected_grade):
    filtered_df = df[df['Grade'] == selected_grade]
    fig.update_traces(y=[filtered_df['min'].iloc[0], filtered_df['max'].iloc[0]])
    fig.update_layout(title=f'min and max Plot for Grade {selected_grade}')
    clear_output()
    display(grade_dropdown)
    fig.show()

# Dropdown value change event handler
def on_dropdown_change(change):
    update_plot(change['new'])

grade_dropdown.observe(on_dropdown_change, names='value')

# Display the dropdown widget and the initial plot
display(grade_dropdown)
fig.show()