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Autoviz With Streamlit
ASecuritySub-skill of autoviz: AutoViz with Streamlit (+1).
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- Added September 9, 2026
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[](https://www.skillsdirectory.com/skills/vamseeachanta-autoviz-with-streamlit)---
name: autoviz-autoviz-with-streamlit
description: 'Sub-skill of autoviz: AutoViz with Streamlit (+1).'
version: 1.0.0
category: data-analysis
type: reference
scripts_exempt: true
---
# AutoViz with Streamlit (+1)
## AutoViz with Streamlit
```python
import streamlit as st
from autoviz import AutoViz_Class
import pandas as pd
import os
import tempfile
st.set_page_config(page_title="AutoViz EDA Tool", layout="wide")
st.title("AutoViz Exploratory Data Analysis")
# File upload
uploaded_file = st.file_uploader("Upload CSV file", type=["csv"])
if uploaded_file is not None:
df = pd.read_csv(uploaded_file)
st.subheader("Data Preview")
st.dataframe(df.head(100))
col1, col2 = st.columns(2)
with col1:
st.metric("Rows", f"{len(df):,}")
with col2:
st.metric("Columns", len(df.columns))
# Target variable selection
target = st.selectbox(
"Select target variable (optional)",
["None"] + list(df.columns)
)
if st.button("Run AutoViz Analysis"):
with st.spinner("Generating visualizations..."):
# Create temp directory for outputs
with tempfile.TemporaryDirectory() as tmpdir:
AV = AutoViz_Class()
df_analyzed = AV.AutoViz(
filename="",
dfte=df,
depVar="" if target == "None" else target,
chart_format="png",
save_plot_dir=tmpdir,
verbose=0
)
# Display generated charts
st.subheader("Generated Visualizations")
for file in os.listdir(tmpdir):
if file.endswith(".png"):
st.image(os.path.join(tmpdir, file))
st.success("Analysis complete!")
```
## AutoViz with Polars
```python
from autoviz import AutoViz_Class
import polars as pl
import pandas as pd
def autoviz_polars(lf: pl.LazyFrame, target: str = "", **kwargs) -> pd.DataFrame:
"""
Run AutoViz on Polars LazyFrame.
Args:
lf: Polars LazyFrame
target: Target variable name
**kwargs: Additional AutoViz parameters
Returns:
Analyzed DataFrame
"""
# Collect LazyFrame to DataFrame, then convert to pandas
df_polars = lf.collect()
df_pandas = df_polars.to_pandas()
AV = AutoViz_Class()
return AV.AutoViz(
filename="",
dfte=df_pandas,
depVar=target,
**kwargs
)
# Usage
# lf = pl.scan_csv("data.csv")
# df_analyzed = autoviz_polars(lf, target="revenue", chart_format="png")
```
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