Data Visualization in Python with Seaborn Literacy (Beginner Level)

  • 8m
  • 8 questions
The Data Visualization in Python with Seaborn Literacy (Beginner Level) benchmark will measure your ability to recall and relate underlying data visualization concepts using Python and seaborn. You will be evaluated on your ability to recognize the foundational concepts of data visualization, its uses, and best practices. A learner who scores high on this benchmark demonstrates that they have the basic data visualization skills to understand and grasp visualization techniques and their uses.

Topics covered

  • analyze the relationship between two variables by plotting a bivariate distribution
  • configure an univariate distribution's appearance, including color, size, and the components of the plot
  • define and plot the distribution of a single variable using a histogram and kernel density estimate curve
  • describe the basic aesthetic themes and styles available in Seaborn
  • describe what Seaborn is and how it relates to other data science libraries in Python
  • distinguish between scatter plots, hexbin plots, and KDE plots
  • perform a regression analysis on a pair of variables in your dataset by using the Seaborn lmplot
  • use the Seaborn pair plot to generate a grid to plot the relationship between multiple pairs of variables in your dataset