Sub-skill of ydata-profiling: YData Profiling with Streamlit (+1).
Scanned 9/9/2026
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---
name: ydata-profiling-ydata-profiling-with-streamlit
description: 'Sub-skill of ydata-profiling: YData Profiling with Streamlit (+1).'
version: 1.0.0
category: data-analysis
type: reference
scripts_exempt: true
---
# YData Profiling with Streamlit (+1)
## YData Profiling with Streamlit
```python
import streamlit as st
from ydata_profiling import ProfileReport
import pandas as pd
from streamlit_pandas_profiling import st_profile_report
st.set_page_config(page_title="Data Profiler", layout="wide")
st.title("Interactive Data Profiler")
uploaded_file = st.file_uploader("Upload CSV", type=["csv"])
if uploaded_file:
df = pd.read_csv(uploaded_file)
st.subheader("Data Preview")
st.dataframe(df.head(100))
# Profile options
with st.sidebar:
st.header("Profile Options")
minimal = st.checkbox("Minimal Mode", value=False)
explorative = st.checkbox("Explorative Mode", value=True)
if st.button("Generate Profile"):
with st.spinner("Generating report..."):
profile = ProfileReport(
df,
title="Data Profile",
minimal=minimal,
explorative=explorative
)
st_profile_report(profile)
```
## YData Profiling with Polars
```python
from ydata_profiling import ProfileReport
import polars as pl
import pandas as pd
def profile_polars_df(
lf: pl.LazyFrame,
title: str = "Polars Data Profile",
**kwargs
) -> ProfileReport:
"""
Profile Polars LazyFrame using YData Profiling.
Args:
lf: Polars LazyFrame
title: Report title
**kwargs: Additional ProfileReport arguments
Returns:
ProfileReport object
"""
# Collect and convert to pandas
df_polars = lf.collect()
df_pandas = df_polars.to_pandas()
return ProfileReport(df_pandas, title=title, **kwargs)
# Usage
# lf = pl.scan_parquet("data.parquet")
# profile = profile_polars_df(lf, title="Polars Data Profile")
# profile.to_file("profile.html")
```
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