Python for Data Analysis: Step-By-Step with Projects - Modifying Values

Python for Data Analysis: Step-By-Step with Projects - Modifying Values

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

Created by

Quizizz Content

FREE Resource

This video tutorial covers how to modify data frames using pandas. It explains accessing and changing individual data entries, modifying multiple entries based on conditions, adding new rows, changing existing column values, and adding new columns. Techniques such as using loc and iloc for indexing and filtering are demonstrated, along with practical examples like converting height measurements and calculating BMI.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of this lesson on data frames?

Modifying values within existing data frames

Visualizing data frames

Creating new data frames from scratch

Deleting data frames

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which method is used for label-based indexing in pandas?

filter

iloc

loc

index

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can you change all occurrences of a specific value in a column?

Using a for loop

Using the loc property with a condition

Manually editing each entry

Using the iloc property

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens if you try to add a new row using iloc?

It throws an error because iloc cannot enlarge its target

It adds the row successfully

It duplicates the last row

It replaces the first row

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which method is used to select numeric columns in a data frame?

pivot

groupby

filter

select_dtypes

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How can you convert a column's measurement from centimeters to feet?

Divide by 100

Multiply by 0.0328084

Subtract 10

Add 0.5

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the result of multiplying all numeric columns by 100?

It multiplies each element in the numeric columns by 100

It changes the data type to string

It adds 100 new columns

It deletes the numeric columns

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