embedding_model / streamlit_piechart
molehh's picture
add streamlit_piechart
55946c6
import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
from textblob import TextBlob
def load_data(uploaded_file):
# Load Excel file, supports both .xlsx and .xls
try:
df = pd.read_excel(uploaded_file) # Automatically detects file format
df.columns = df.columns.str.strip().str.lower() # Normalize column names
return df
except Exception as e:
st.error(f"Error loading file: {e}")
return None
def analyze_sentiment(text):
polarity = TextBlob(str(text)).sentiment.polarity
if polarity >= 0.6:
return "Very Positive"
elif polarity >= 0.2:
return "Positive"
elif polarity > -0.2:
return "Neutral"
elif polarity > -0.6:
return "Negative"
else:
return "Very Negative"
st.title("Sentiment Analysis with Pie Chart")
# File uploader supports .xlsx and .xls
uploaded_file = st.file_uploader("Upload an Excel file with text data", type=["xlsx", "xls"])
if uploaded_file is not None:
df = load_data(uploaded_file)
if df is not None:
st.write("Columns in your file:", df.columns.tolist())
# Allow the user to select a column if 'text' is not already present
if "text" not in df.columns:
selected_column = st.selectbox("Select the column to use as text data:", df.columns)
if st.button("Confirm Selection"):
df.rename(columns={selected_column: "text"}, inplace=True)
st.success(f"Column '{selected_column}' renamed to 'text'.")
if "text" in df.columns: # Check again if 'text' column is present after renaming
df["Sentiment"] = df["text"].apply(analyze_sentiment)
st.write("Here is a preview of the data:")
st.write(df.head())
sentiment_counts = df["Sentiment"].value_counts()
fig, ax = plt.subplots()
ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct="%1.1f%%", colors=["green", "lightgreen", "gray", "orange", "red"])
ax.set_title("Sentiment Distribution")
st.pyplot(fig)
# Export processed data to Excel file (.xlsx) without explicitly using xlsxwriter
output_file = "sentiment_results.xlsx"
df.to_excel(output_file, index=False, sheet_name="Sentiment Analysis")
# Download button for Excel file
with open(output_file, "rb") as f:
st.download_button(
"Download Sentiment Data (Excel)",
f,
"sentiment_results.xlsx",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
)
else:
st.warning("Please select a column to rename as 'text' and proceed.")
else:
st.write("Please upload an Excel file to get started.")