📊 Day 40: Likert Scale Chart in Python

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🔹 What is a Likert Scale Chart?

A Likert Scale Chart is used to show survey responses like:

• Strongly Agree

• Agree

• Neutral

• Disagree

• Strongly Disagree

It helps visualize opinions or satisfaction levels.

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🔹 When Should You Use It?

Use a Likert chart when:

• Analyzing survey results

• Measuring customer satisfaction

• Collecting employee feedback

• Getting product reviews

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🔹 Example Scenario

Survey Question:
"Are you satisfied with our service?"

Responses:

• Strongly Disagree → 5

• Disagree → 10

• Neutral → 15

• Agree → 40

• Strongly Agree → 30

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🔹 Python Code (Horizontal Likert Chart – Plotly)

import plotly.graph_objects as go

categories = ["Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"] 
values = [5, 10, 15, 40, 30] 

fig = go.Figure() 
fig.add_trace(go.Bar(
    y=["Customer Satisfaction"] * len(categories),
    x=values,
    orientation='h',
    text=categories,
    hoverinfo='text+x',
  marker=dict(color=["#BC6C25", "#DDA15E", "#E9C46A", "#90BE6D", "#2A9D8F"])
))

fig.update_layout(
 title="Customer Satisfaction Survey",
    barmode='stack',
    paper_bgcolor="#FAF9F6",
    plot_bgcolor="#FAF9F6", 
    xaxis_title="Number of Responses", 
    showlegend=False, 
    width=800,
    height=300
)

fig.show()

📌 Install if needed:

pip install plotly

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🔹 Output Explanation (Beginner Friendly)

• Each color represents a response type.

• The length of each section shows how many people selected that option.

• Green shades usually mean positive responses.

• Brown/orange shades represent negative responses.

👉 You can quickly see if most people are satisfied or not.
👉 In this example, most responses are positive (Agree + Strongly Agree).

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🔹 Why Likert Charts Are Useful

✅ Easy to understand
✅ Great for survey reports
✅ Perfect for dashboards
✅ Visually shows overall sentiment