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Seaborn_Visualizations.ipynb

Code

# Anscombe Quartet

import seaborn as sns

sns.set_theme(style = "darkgrid")

Anscombe_Dt = sns.load_dataset("anscombe")

sns.lmplot(data= Anscombe_Dt, x= "x", y="y",
           hue= "dataset",col = "dataset", col_wrap=2, palette= "muted",
           ci=None,height=4, scatter_kws={"s": 50, "alpha": 1})

Anscombe_Dt.head()

• data: The DataFrame to use (in this case, Anscombe_Dt).
• x: The variable to be plotted on the x-axis.
• y: The variable to be plotted on the y-axis.
• hue: Grouping variable that will produce points with different colors. Here, it's based on the "dataset" column.
• col: Variable that will produce separate columns within the grid for different values. This will create separate plots for each "dataset".
• col_wrap: Number of columns in the grid before wrapping to a new row.
• palette: Color palette to use for the different levels of the hue variable.
• ci: Confidence interval for the regression estimate. None in this case.
• height: Height (in inches) of each facet.
• scatter_kws: Additional keyword arguments to pass to plt.scatter and plt.plot.