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import streamlit as st
import pandas as pd
import json
def render_dataset_preview(dataset, dataset_type):
"""
Renders a preview of the dataset with pagination options.
Args:
dataset: The dataset to preview (pandas DataFrame)
dataset_type: The type of dataset (csv, json, etc.)
"""
if dataset is None:
st.warning("No dataset to preview.")
return
st.markdown(f"<h3>Dataset Preview: {st.session_state.dataset_name}</h3>", unsafe_allow_html=True)
# Show basic info
col1, col2, col3 = st.columns(3)
with col1:
st.metric("Rows", f"{dataset.shape[0]:,}")
with col2:
st.metric("Columns", f"{dataset.shape[1]:,}")
with col3:
st.metric("Type", dataset_type.upper())
# Preview options
col1, col2 = st.columns([1, 3])
with col1:
num_rows = st.number_input("Rows to display", min_value=5, max_value=100, value=10, step=5)
with col2:
preview_mode = st.radio("Preview mode", ["Head", "Tail", "Sample"], horizontal=True)
# Display dataset preview
st.markdown("<div class='dataset-preview'>", unsafe_allow_html=True)
if preview_mode == "Head":
st.dataframe(dataset.head(num_rows), use_container_width=True)
elif preview_mode == "Tail":
st.dataframe(dataset.tail(num_rows), use_container_width=True)
else: # Sample
st.dataframe(dataset.sample(min(num_rows, len(dataset))), use_container_width=True)
st.markdown("</div>", unsafe_allow_html=True)
# Show dataset schema
with st.expander("Dataset Schema"):
col1, col2 = st.columns(2)
with col1:
st.markdown("**Column Types**")
type_df = pd.DataFrame({
'Column': dataset.dtypes.index,
'Type': dataset.dtypes.values.astype(str)
})
st.dataframe(type_df, use_container_width=True)
with col2:
st.markdown("**Missing Values**")
missing_df = pd.DataFrame({
'Column': dataset.columns,
'Missing': dataset.isna().sum().values,
'Percentage': dataset.isna().sum().values / len(dataset) * 100
})
st.dataframe(missing_df.style.format({
'Percentage': '{:.2f}%'
}), use_container_width=True)
# Raw data
with st.expander("Raw Data (First 5 records)"):
if dataset_type == 'csv':
st.code(dataset.head(5).to_csv(index=False), language="text")
else: # json or jsonl
st.code(dataset.head(5).to_json(orient='records', indent=2), language="json")
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