Python for Data Analysis: Step-By-Step with Projects - Distribution of One Feature

Python for Data Analysis: Step-By-Step with Projects - Distribution of One Feature

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

This lesson covers data visualization techniques for exploring the distribution of numerical and categorical features. It introduces methods like describe, histograms, box plots, and KDE plots for numerical data, and value counts and bar plots for categorical data. The lesson emphasizes understanding data distributions and the importance of visualizations in data analysis.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the first step in exploring data through visualizations?

Analyzing relationships between multiple columns

Exploring the distribution of a single feature

Using machine learning algorithms

Creating complex visualizations

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which method is commonly used to summarize numerical data?

Bar plot

Describe method

Scatter plot

Value counts

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a histogram primarily show?

The median of the data

The mean of the data

The distribution of data

The correlation between variables

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key characteristic of a skewed right distribution?

Longer left tail

Symmetrical shape

Equal peaks

Longer right tail

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a KDE plot?

A scatter plot

A smoother version of a histogram

A method to calculate mean

A type of bar plot

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can you explore the distribution of a categorical feature?

Using histograms

Using scatter plots

Using the describe method

Using value counts

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the value counts method provide?

Mean and median values

Correlation coefficients

Unique categories and their counts

Summary statistics

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