EDA Python - 19-Pandas_3

EDA Python - 19-Pandas_3

Assessment

Interactive Video

•

Information Technology (IT), Architecture, Social Studies

•

University

•

Practice Problem

•

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers data analysis using Python, focusing on loading, cleaning, and transforming data with pandas. It demonstrates how to use pivot tables for data transformation and create visualizations using both pandas and Matplotlib. The tutorial also includes specific analysis of COVID-19 data, particularly focusing on the UK and top five countries by case count. It concludes with efficient methods for loading and saving data.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of using the OS module in the notebook?

To import data from CSV files

To create file paths independent of the operating system

To style the plots

To execute Python scripts

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is whitespace removed from column headings in a DataFrame?

By converting the column to a string

By reloading the DataFrame

Using the strip method in a list comprehension

Using the replace method

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the benefit of converting a column to a datetime data type?

It allows for time series analysis

It reduces memory usage

It improves data accuracy

It changes the data format to string

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the pivot function in Pandas do?

It filters the DataFrame

It merges two DataFrames

It sorts the DataFrame

It reshapes the DataFrame by turning unique values into columns

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which library provides more granular control over plot appearance?

Pandas

NumPy

Matplotlib

SciPy

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can you create a horizontal bar chart in Matplotlib?

Using the plot function

Using the barh function

Using the scatter function

Using the line function

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of using a mask in data filtering?

To filter data based on a condition

To highlight data

To sort data

To merge data

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