Python Statistical Plots: Time Series Data & Regression Analysis in Seaborn
Python 3.8
| Intermediate
- 13 Videos | 1h 33m 30s
- Includes Assessment
- Earns a Badge
Seaborn's smartly designed interface lets you illuminate data through aesthetically pleasing statistical graphics that are incredibly easy to build. In this course, you'll discover Seaborn's capabilities. You'll begin using strip plots and swarm plots and recognizing how they work together using low-intensity noise. You'll then work with time series data through various techniques, like resampling data at different time frequencies and plotting with confidence intervals and other types of error bars. Next, you'll visualize both logistic and linear regression curves. Moving on, you'll use the pairplot function to visualize the relationships between columns in your data, taken two at a time, in a grid format. You'll change the chart type being visualized and create pair plots with multiple chart types in each plot. Lastly, you'll create and format a heatmap of a correlation matrix to identify relationships between dataset columns.
WHAT YOU WILL LEARN
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discover the key concepts covered in this course
create custom figure-level and axis-level strip plots
contrast strip plots and swarm plots
visualize time series data using figure-level and axis-level line charts
perform operations on time series data
create custom line charts visualizing time series data
use the axis-level regplot() and figure-level lmplot() for regression plots -
use the hue, col, and row input arguments to categorize regression plots
apply logistic regressions to categorical data
create pair plots to visualize multivariate relationships
customize pair plots with KDE curves, regression plots, and contour maps
create custom heatmaps to visualize correlation matrices
summarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview2m 45sUP NEXT
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2.Creating Strip Plots9m 18s
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3.Creating Swarm Plots8m 51s
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4.Visualizing Basic Time Series Data7m 21s
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5.Performing Time Series Operations7m 21s
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6.Creating Line Charts6m 2s
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7.Visualizing Relationships Using Regression Plots8m 51s
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8.Customizing Regression Plots Using Categories9m 29s
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9.Applying Logistic Regression7m 31s
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10.Creating Pair Plots8m 2s
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11.Customizing Pair Plots8m 56s
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12.Visualizing Correlation Matrices with Heatmaps6m 17s
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13.Course Summary2m 48s
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