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Data Science Interview Challenge
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Data Science Interview Challenge

Data Science Interview Challenge

1. Python
IntroductionChallenge 1: List ComprehensionChallenge 2: String ManipulationChallenge 3: Dictionary ManipulationChallenge 4: Nested LoopsChallenge 5: ClassesTheoretical Questions
2. NumPy
Challenge 1: Array CreationChallenge 2: Array ManipulationChallenge 3: Statistical InsightsChallenge 4: Handling Missing ValuesChallenge 5: Subarray SortingTheoretical Questions
3. Pandas
Challenge 1: DataFrame CreationChallenge 2: Data GroupingChallenge 3: Indexing and MultiIndexingChallenge 4: Altering DataFrameChallenge 5: Iterating Over DataTheoretical Questions
4. Matplotlib
Challenge 1: Fundamentals of PlottingChallenge 2: Other Graph TypesChallenge 3: SubplotsChallenge 4: Customizing PlotsChallenge 5: Adding Text to PlotsTheoretical Questions
5. Seaborn
Challenge 1: Visualizing DistributionsChallenge 2: Exploring Categorical DataChallenge 3: Relational PlotsChallenge 4: Regression PlotsChallenge 5: Matrix PlotsTheoretical Questions
6. Statistics
Challenge 1: Probabilities and DistributionsChallenge 2: Bayes' TheoremChallenge 3: Hypothesis TestingChallenge 4: Confidence IntervalsChallenge 5: CorrelationTheoretical Questions
7. Scikit-learn
Challenge 1: Data ScalingChallenge 2: Basic Model CreationChallenge 3: PipelinesChallenge 4: Cross-validationChallenge 5: Hyperparameter TuningTheoretical Questions

book
Challenge 1: Visualizing Distributions

Understanding how data is distributed is fundamental in the data analysis process. Distributions help us to visualize the central tendencies, variability, and the presence of any outliers in our dataset. Seaborn, a statistical plotting library built on top of Matplotlib, provides a suite of tools that makes visualizing distributions a breeze.

The various plots and tools under Seaborn's distribution utilities can:

  • Examine the distribution of a dataset.
  • Visualize the relationship between multiple variables.
  • Display the underlying probability distributions of datasets.

Using Seaborn to create distribution plots ensures that the viewer can get a comprehensive view of the data's distribution and its characteristics.

Taak

Swipe to start coding

Using Seaborn, visualize the distribution of a dataset:

  1. Plot a univariate distribution of data using a histogram and overlay it with a kernel density estimate (KDE).
  2. Visualize the bivariate distribution between two variables using a scatter plot and include a KDE plot to see the data's density.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 5. Hoofdstuk 1
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book
Challenge 1: Visualizing Distributions

Understanding how data is distributed is fundamental in the data analysis process. Distributions help us to visualize the central tendencies, variability, and the presence of any outliers in our dataset. Seaborn, a statistical plotting library built on top of Matplotlib, provides a suite of tools that makes visualizing distributions a breeze.

The various plots and tools under Seaborn's distribution utilities can:

  • Examine the distribution of a dataset.
  • Visualize the relationship between multiple variables.
  • Display the underlying probability distributions of datasets.

Using Seaborn to create distribution plots ensures that the viewer can get a comprehensive view of the data's distribution and its characteristics.

Taak

Swipe to start coding

Using Seaborn, visualize the distribution of a dataset:

  1. Plot a univariate distribution of data using a histogram and overlay it with a kernel density estimate (KDE).
  2. Visualize the bivariate distribution between two variables using a scatter plot and include a KDE plot to see the data's density.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 5. Hoofdstuk 1
Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Onze excuses dat er iets mis is gegaan. Wat is er gebeurd?
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