Handling Bulk Timestamp Conversions in Data Pipelines
Engineers, data analysts, and DevOps teams frequently extract server logs, database exports, and event streaming dumps that contain thousands of raw numeric timestamps. Parsing these individual records manually is tedious; our Batch Converter automates high-speed translation directly in your browser.
1. Multi-line Paste
Paste hundreds of newline-separated or comma-separated timestamps at once.
2. Auto-Detect Units
Each row is automatically validated for seconds (10 digits) or milliseconds (13 digits).
3. One-Click Export
Download clean CSV or JSON structures ready to import into Excel, Python, or SQL.
Bulk Timestamp Parsing in Python (Pandas) & JavaScript
Python / Pandaspd.to_datetime()
import pandas as pd
# List of Unix timestamps (seconds)
timestamps = [1730100000, 1730110000, 1730120000]
# Vectorized conversion to UTC datetime
df = pd.DataFrame({'epoch': timestamps})
df['datetime_utc'] = pd.to_datetime(df['epoch'], unit='s', utc=True)
print(df)JavaScript / Node.jsArray.map() Transformation
const timestamps = [1730100000, 1730110000, 1730120000];
const convertedRows = timestamps.map(ts => ({
epoch: ts,
iso: new Date(ts * 1000).toISOString(),
local: new Date(ts * 1000).toLocaleString()
}));
console.table(convertedRows);