TabLab

Excel Viewer and Editor

Open, view, and edit Excel files (.xlsx, .xls) with our interactive viewer and editor. Convert to CSV or other formats for advanced analysis and visualization.

Format
Click anywhere to select a fileor drag and drop a file here
Accepts Excel file (.xlsx, .xls)
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Excel Viewer Features

Edit data cells
Modify values directly in your Excel files and download the updated file
Formula support
View and edit Excel formulas with cached values
Interactive data grid
View your data in a structured, easy-to-read format with Excel-like interface
Smart data understanding
Convert to table format for AI analysis of patterns and relationships in your Excel data
Lightning-fast performance
Open and analyze even large Excel files instantly
Sort functionality
Use "View as Table" to arrange data by any column in ascending or descending order
Advanced filtering
Use "View as Table" to filter rows based on multiple column values and conditions
Aggregation capabilities
Use "View as Table" to perform sum, average, count and other calculations on your data
AI-powered analysis
Use "View as Table" to ask questions about your Excel data in plain English and get instant insights

How to view and edit Excel files online

  1. Upload your Excel file (.xlsx or .xls) by clicking the upload button or dragging and dropping
  2. View your data in an interactive spreadsheet with formula support
  3. Edit cells directly by clicking on them - changes are saved to the file
  4. Click "View as Table" to access advanced features like AI chat, filtering, and sorting
  5. Use the AI chat to ask questions about your data and get insights (requires "View as Table")
  6. Download the modified Excel file when you're done editing

How to view Excel files in Python

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

Viewing Excel files with Pandas

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

First, we need to install pandas

pip install pandas

Then we can load and view the xlsx file

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

Viewing Excel files with DuckDB

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

DuckDB supports Excel files directly through the excel extension:

pip install duckdb

Query Excel files directly with DuckDB:

import duckdb
# Install and load the excel extension
conn = duckdb.connect()
conn.execute("INSTALL excel")
conn.execute("LOAD excel")
# Query Excel file directly
result = conn.execute("SELECT * FROM 'path/to/file.xlsx' LIMIT 10").fetchdf()
print(result)

For more control, use the read_xlsx function:

# Read specific sheet with options
result = conn.execute("SELECT * FROM read_xlsx('path/to/file.xlsx', header=true, sheet='Sheet1') LIMIT 10").fetchdf()
print(result)

Viewing Excel files with ClickHouse

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

ClickHouse doesn't support Excel files directly. First convert to CSV using pandas:

pip install pandas clickhouse-connect

Convert Excel to CSV, then load into ClickHouse:

import pandas as pd
import clickhouse_connect
# Convert Excel to CSV first
df = pd.read_excel('path/to/file.xlsx')
df.to_csv('temp_file.csv', index=False)
# Now query with ClickHouse
client = clickhouse_connect.get_client(host='localhost', port=8123)
query = "SELECT * FROM file('temp_file.csv') LIMIT 10"
result = client.query(query).result_set
print(result)