Hiring Seaborn developers? Then you should know!
How and where is Seaborn used?
- Statistical Data Visualization: Analyzing trends
- Linear Relationships: Visualizing linear relationships
- Distribution of Data: Analyzing data distribution
- Categorical Data: Plotting categorical data
- Multi-plot Grids: Creating multi-plot grids
- Pairwise Relationships: Visualizing pairwise relationships
- Regression Analysis: Performing regression analysis
- Time Series Visualization: Visualizing time series data
- Customizing Plots: Customizing plot aesthetics
- Anomaly Detection: Detecting outliers in data
Compare Junior, Middle, Senior, and Expert/Team Lead Seaborn Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 0-2 years |
| $60,000 |
Middle | 2-4 years |
| $80,000 |
Senior | 4-6 years |
| $100,000 |
Expert/Team Lead | 6+ years |
| $120,000 |
Quick Facts about Seaborn.
- Seaborn was conjured up in the mystical land of Python in the year 2012.
- It’s the go-to sorcery for crafting enchanting statistical data visualizations.
- To unlock the powers of Seaborn, one must possess basic Python wizardry skills.
- Pandas, the friendly giant of data manipulation, often teams up with Seaborn.
- Rumor has it that Seaborn’s color palettes were inspired by unicorns and rainbows.
TOP Seaborn Related Technologies
- Matplotlib (John D. Hunter, 2003)
- Pandas (Wes McKinney, 2008)
- Numpy (Travis Oliphant, 2005)
- Scikit-learn (David Cournapeau, 2007)
- Plotly (Plotly Technologies Inc., 2015)
What are top Seaborn instruments and tools?
- Seaborn: Data visualization library for Python released by Michael Waskom in 2012
- Seaborn-Palette: Tool for custom color palettes provided by Seaborn team in 2017
- Seaborn-Grid: Grid control utility released by Seaborn developers in 2015
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