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import datahorse
import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import io
import sys
st.title('Text to Data Analysis')
# Initialize session state for conversation history
if 'conversation' not in st.session_state:
st.session_state.conversation = []
uploaded_file = st.file_uploader('Upload .csv data: ')
query = st.text_input('Search about data: ')
def capture_output(func):
# Capture stdout
old_stdout = sys.stdout
new_stdout = io.StringIO()
sys.stdout = new_stdout
# Capture matplotlib figures
fig = plt.figure()
result = func()
# Reset stdout
sys.stdout = old_stdout
output = new_stdout.getvalue()
# Check if a plot was created
if plt.gcf().axes:
return fig
elif output:
return output
else:
return result
if uploaded_file is not None:
# Add some example queries
st.sidebar.header("Example Queries")
st.sidebar.write("1. Show me a summary of the data")
st.sidebar.write("2. Create a bar chart of [column_name]")
st.sidebar.write("3. What is the average of [column_name]?")
st.sidebar.write("4. Show me the correlation between [column1] and [column2]")
st.sidebar.write("5. List the unique values in [column_name]")
st.sidebar.write("6. What is the maximum value in [column_name]?")
st.sidebar.write("7. Create a line chart of [column_name] over time")
st.sidebar.write("8. How many missing values are in [column_name]?")
st.sidebar.write("9. Filter rows where [column_name] is greater than [value]")
st.sidebar.write("10. Generate a pie chart for [column_name]")
df = datahorse.read(uploaded_file)
col1, col2 = st.columns(2)
if col1.button('Search it'):
# Append user query to conversation history
user_message = f"""
<div style='background-color: #f0f0f0; padding: 10px; border-radius: 10px; margin: 5px 0;'>
<strong>Me:</strong> {query}
</div>
"""
st.session_state.conversation.append(user_message)
# Get response from datahorse
response = capture_output(lambda: df.chat(query))
st.subheader("Response:")
if isinstance(response, plt.Figure):
st.pyplot(response)
elif isinstance(response, str):
st.text(response)
elif isinstance(response, pd.DataFrame):
st.dataframe(response)
elif response is not None:
st.write(response)
else:
st.write("No output was captured.")
# Append response to conversation history
response_message = f"""
<div style='background-color: #4CAF50; color: white; padding: 10px; border-radius: 10px; margin: 5px 0;'>
<strong>Datahorse:</strong> Response displayed above
</div>
"""
st.session_state.conversation.append(response_message)
# Clear conversation history
if col2.button('Clear Conversation'):
st.session_state.conversation = []
# Display conversation history
for message in reversed(st.session_state.conversation):
st.markdown(message, unsafe_allow_html=True)
# Display the dataframe
if uploaded_file is not None:
st.write("Preview of the uploaded data:")
st.dataframe(df.head())
# Display column names
st.write("Column names in the dataset:")
st.write(", ".join(df.columns)) |