AI CSV Viewer

How to view CSV files online

1. Upload your CSV file by clicking the "Open CSV file" button or dragging and dropping it into the upload area.
2. Once uploaded, your data will be displayed in an interactive grid where you can scroll through rows and resize columns.
3. Use the filter controls to narrow down your data by applying filters to multiple columns simultaneously.
4. Sort your data by clicking on any column header.
5. For advanced analysis, use the SQL editor to write custom queries on your CSV data, including complex filtering and advanced operations like multi-column sorting.
6. Ask questions about your data in plain English using our AI assistant to get instant insights without writing complex queries.
7. When you're done analyzing, you can export your data or filtered results in various formats.

How to view CSV files in Python

Here are three effective ways to view CSV files in Python using different libraries. Each approach has its own advantages depending on your specific needs and file sizes.

Viewing CSV files with Pandas

Pandas provides a straightforward approach for viewing files and works well for most common data tasks:

pip install pandas

import pandas as pd
df = pd.read_csv('path/to/file.csv')
print(df.head())

Viewing CSV files with DuckDB

DuckDB is an in-process SQL OLAP database that's perfect for larger files and analytical workloads:

pip install duckdb

import duckdb
result = duckdb.sql(f"SELECT * FROM 'path/to/file.csv' LIMIT 10").fetchdf()
print(result)

Viewing CSV files with ClickHouse

ClickHouse is a high-performance column-oriented database system that's excellent for large-scale data processing:

pip install clickhouse-connect

import clickhouse_connect
client = clickhouse_connect.get_client(host='localhost', port=8123)
query = f"SELECT * FROM file('path/to/file.csv') LIMIT 10"
result = client.query(query).result_set
print(result)