Add Likert data vizualisations

app.py

@@ -1,4 +1,159 @@
 import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Streamlit title and introduction
+st.title("Likert Scale Visualizations")
+st.write("This app visualizes responses to a survey.")
+
+# Upload the CSV file
+uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
+
+if uploaded_file is not None:
+    # Load the CSV file into a DataFrame
+    df = pd.read_csv(uploaded_file)
+
+    likert_fields = {
+        '購物習慣': [
+            '如果你/妳懷疑你/妳要買的番茄可能是由強迫勞工（現代奴隸）採摘的，你/妳仍然會買它嗎？',
+            '你/妳關心食安嗎？',
+            '你/妳7年內買車嗎？🚘',
+            '你/妳7年內買房嗎？🏡',
+            '你/妳購物時知道產品環保嗎？',
+            '你/妳覺得認證環保的公司更好嗎？',
+            '你/妳支持肉稅嗎？',
+            '你/妳關心食用雞的生活嗎？',
+            '你/妳避免吃肉嗎？',
+            '你/妳覺得你/妳花錢會影響環境嗎？'
+        ],
+        '存錢和投資習慣': [
+            '你/妳會對金錢感到焦慮嗎？',
+            '你/妳會對金錢很節儉嗎？',
+            '你/妳會經常存錢嗎？',
+            '你/妳對自己的財務知識滿意嗎？',
+            '你/妳投資會考慮環保嗎？'
+        ],
+        '台灣的經濟': [
+            '你/妳覺得台灣的經濟目標是增長嗎？',
+            '你/妳覺台灣的得環境退化是台灣的經濟增長的前提嗎？',
+            '你/妳覺得台灣的經濟增長有助於保護環境嗎？',
+            '你/妳覺得經濟能不排CO2也增長嗎？',
+            '你/妳覺得經濟增長有物質限制嗎？'
+        ],
+        'AI使用習慣': [
+            '你/妳會每天都用AI嗎？',
+            '你/妳會信任AI嗎？',
+            '你/妳想要AI有個造型嗎？',
+        ],
+        '台灣的大自然': [
+            '你/妳喜歡待在大自然嗎？',
+            '你/妳擔心氣候變化嗎？',
+            '你/妳對環境污染情況會感到焦慮嗎？',
+            '你/妳知道許多植物和動物的名字嗎？',
+            '你/妳感覺自己和大自然很接近嗎？'
+        ],
+        '環保習慣': [
+            '你/妳努力實踐低碳生活嗎？',
+            '你/妳想做更多環保事嗎？',
+            '你/妳對環境相關政治議題有興趣嗎？',
+            '你/妳信任碳排放抵消額度嗎？',
+            '你/妳的環保行動對環境保護有效果嗎？',
+            '你/妳想在行業內推環保嗎？'
+        ],
+        '學習環境': [
+            '你/妳得自己對新觀念開放嗎？',
+            '你/妳的大學對可環保性支持嗎？'
+        ]
+    }
+
+    # Translation mapping for the categories
+    translation_mapping = {
+        '購物習慣': 'Shopping Habits',
+        '存錢和投資習慣': 'Saving and Investing Habits',
+        '台灣的經濟': "Taiwan's Economy",
+        'AI使用習慣': 'AI Usage Habits',
+        '台灣的大自然': "Taiwan's Natural Environment",
+        '環保習慣': 'Environmental Habits',
+        '學習環境': 'Learning Environment'
+    }
+
+    # Translation mapping for the field names in each category (this should match your actual field names)
+    field_translation_mapping = {
+        '購物習慣': [
+            "Would you still buy a tomato if you suspected it was picked by forced labor?",
+            "Do you care about food safety?",
+            "Will you buy a car within 7 years?",
+            "Will you buy a house within 7 years?",
+            "Do you know if the product is environmentally friendly when shopping?",
+            "Do you think companies with environmental certifications are better?",
+            "Do you support a meat tax?",
+            "Do you care about the living conditions of chickens you consume?",
+            "Do you avoid eating meat?",
+            "Do you think your spending affects the environment?"
+        ],
+        '存錢和投資習慣': [
+            "Do you feel anxious about money?",
+            "Are you frugal with money?",
+            "Do you save money regularly?",
+            "Are you satisfied with your financial knowledge?",
+            "Do you consider environmental impact when investing?"
+        ],
+        '台灣的經濟': [
+            "Do you think the economic goal of Taiwan is growth?",
+            "Do you think that environmental degradation is a prerequisite for Taiwan's economic growth?",
+            "Do you think Taiwan's economic growth contributes to environmental protection?",
+            "Do you think the economy can grow without emitting CO2?",
+            "Do you think economic growth has material limits?"
+        ],
+        'AI使用習慣': [
+            "Do you use AI every day?",
+            "Do you trust AI?",
+            "Would you like AI to have a form?"
+        ],
+        '台灣的大自然': [
+            "Do you like to be in nature?",
+            "Are you worried about climate change?",
+            "Do you feel anxious about environmental pollution?",
+            "Do you know the names of many plants and animals?",
+            "Do you feel close to nature?"
+        ],
+        '環保習慣': [
+            "Do you strive to live a low-carbon life?",
+            "Would you like to do more for the environment?",
+            "Are you interested in environmental political issues?",
+            "Do you trust carbon offset credits?",
+            "Do you think your environmental actions are effective for environmental protection?",
+            "Would you like to promote environmental protection in your industry?"
+        ],
+        '學習環境': [
+            "Are you open to new ideas?",
+            "Does your university support sustainability?"
+        ]
+    }
+
+    # Rename the columns in the DataFrame for visualization
+    df_translated = df.rename(columns={
+        field: f"{field} ({field_translation_mapping[category][i]})"
+        for category, fields in likert_fields.items()
+        for i, field in enumerate(fields)
+    })
+
+    # Loop through each category in likert_fields to create visualizations
+    for category, fields in likert_fields.items():
+        st.subheader(f'Distribution of Responses for {translation_mapping[category]}')
+
+        # Loop through each field in the category to create individual bar plots
+        for i, field in enumerate(fields):
+            fig, ax = plt.subplots()
+
+            # Create the bar plot
+            sns.countplot(x=f"{field} ({field_translation_mapping[category][i]})", data=df_translated, ax=ax)
+
+            # Add title and labels
+            ax.set_title(field_translation_mapping[category][i])
+            ax.set_xlabel('Likert Scale')
+            ax.set_ylabel('Frequency')
+
+            # Show the plot in Streamlit
+            st.pyplot(fig)