NMR Spectrum
Chart overview
NMR spectrum plots display signal intensity against chemical shift in parts per million, enabling structural elucidation of organic and inorganic compounds.
Key points
- Researchers annotate multiplet patterns, coupling constants, and integration regions to confirm molecular identity and purity.
- These figures are standard in synthetic chemistry, metabolomics, and pharmaceutical characterization workflows.
Python Tutorial
How to create a nmr spectrum in Python
Use the full tutorial for implementation details, troubleshooting, and chart variations in matplotlib, seaborn, and plotly.
Complete Guide to Scientific Data VisualizationExample Visualization
Create This Chart Now
Generate publication-ready nmr spectrums with AI in seconds. No coding required – just describe your data and let AI do the work.
View example prompt
"Create an NMR spectrum plot from my data. Plot chemical shift (ppm) on the x-axis (reversed, high to low) and signal intensity on the y-axis. Annotate the tallest peaks with their ppm values, add integration curves above the baseline, and use journal formatting with Arial font, no top or right spines, and a clean baseline at zero."
How to create this chart in 30 seconds
Upload Data
Drag & drop your Excel or CSV file. Plotivy securely processes it in your browser.
AI Generation
Our AI analyzes your data and generates the NMR Spectrum code automatically.
Customize & Export
Tweak the design with natural language, then export as high-res PNG, SVG or PDF.
Newsletter
Get one weekly tip for better nmr spectrums
Join researchers receiving concise Python plotting techniques to improve chart clarity and reduce revision cycles.
Python Code Example
Console Output
Figure saved: plotivy-nmr-spectrum.png
Common Use Cases
- 1Confirming the structure and purity of synthesized organic compounds
- 2Quantifying metabolite concentrations in NMR-based metabolomics studies
- 3Characterizing pharmaceutical active ingredients and impurity profiling
- 4Monitoring reaction progress and conversion rates in real-time NMR experiments
Pro Tips
Reverse the x-axis so chemical shift decreases left to right, matching standard NMR convention
Add a flat baseline subtraction before plotting to reduce baseline drift artifacts
Use scipy.signal.find_peaks to automatically annotate significant peaks with their ppm values
Include a solvent residual peak marker and reference standard (TMS at 0 ppm) for reproducibility
Long-tail keyword opportunities
High-intent chart variations
Library comparison for this chart
matplotlib
Best when you need full control over axis formatting, annotation placement, and journal-specific styling for nmr-spectrum.
numpy
Useful in specialized workflows that complement core Python plotting libraries for nmr-spectrum analysis tasks.
scipy
Useful in specialized workflows that complement core Python plotting libraries for nmr-spectrum analysis tasks.
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.