.csv
Raw Data
Full Support
Export measurement data and results in CSV format for analysis
Measurement values, timestamps, sample identifiers, method parameters
Analyze Sartorius Entris II data with AI
Analytical/Precision Balance for pharma, biotech, academic, chemical applications
Key Features:
High accuracy, isoCAL automatic calibration, intuitive display, multiple built-in applications, PC-direct data transfer
Industry Applications:
Pharma, biotech, academic, chemical
Target Users:
Lab technician; QC analyst; Researcher
Export Method:
USB (PC direct or USB flash)
Export Formats:
CSV, TXT
Get Started For Free
Fully compatible with Sourcetable
Quick Start Integration
Get your Entris II data into Sourcetable in 3 simple steps
-
Export Data
Export your results from Entris II as CSV, TXT format. Current process typically takes 15 min.
-
Upload to Sourcetable
Import your data directly into Sourcetable for analysis. Our streamlined process reduces analysis time significantly.
-
Start Analysis
Perform automated analysis and generate comprehensive reports. Complete analysis now takes just 5 min.
File Format Compatibility
Entris II provides comprehensive data export capabilities for analytical/precision balance and statistical analysis integration.
.txt
Text Export
Supported
Simple text format export of measurement results
Basic measurement data, readouts, simple formatting
Pre-built Analysis Workflows
Entris II enables advanced analytical workflows for pharma, biotech, academic, chemical applications.
📊
Weight calibration stats
Weight calibration stats
⚗️
Trend analysis of sample weights
Trend analysis of sample weights
📈
Formulation calculations
Formulation calculations
Technical Requirements
Software Dependencies
- Entris II High accuracy, isoCAL automatic calibration, intuitive display, multiple built-in applications, PC-direct data transfer
- File Export Format CSV, TXT
- Export Method USB (PC direct or USB flash)
- Applications Pharma, biotech, academic, chemical
Sourcetable Libraries
- Data Processing pandas, numpy
- Statistical Analysis scipy, statsmodels
- Visualization matplotlib, plotly
- Specialized Analysis pandas, numpy
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