Review · Choose and build · Data Playground

Choose and build · VR1 · 12 MIN

Review · Choose and build

Task 1 · Retrieve and combine

Exercises within this concept

Task 1Retrieve and combineCurrent exercise
Task 2Retrieve and combine
Task 3Retrieve and combine

Task 1 · Movie night

Using df, a cinema wants to see which genres occur most often.

The editable setup on the right creates df. Run executes the setup and your work from top to bottom.

Your requirements

Choose "scatter", "histogram", "counts" or "line".
Write the choice as a Python string.

Your inputs

Movie night · 6 synthetic rows
movie	genre	minutes	rating	screen
Moon	Drama	90	3.7	One
River	Comedy	105	4.2	One
Spark	Drama	112	4.8	Two
Stone	Action	98	4	Two
Map	Comedy	85	3.9	One
Cloud	Action	120	4.5	Two

Revisit the concept lesson →

Remember the idea

Choose a chart from the question and the types of data. Decide what each mark should represent before writing plotting code.

A small example

“Do longer study times go with higher scores?” compares two measurements per person, so one point per person is useful.

What each choice does
Code or choice	Meaning
`"scatter"`	Relationship between two numeric measurements.
`"histogram"`	Distribution of one numeric measurement.
`"counts"`	Frequency of category labels.
`"line"`	Change along an ordered sequence such as time.

Hint

Genres are categories; the question asks about their frequencies.

Reveal solution

One way to do it. Keep any supplied setup in the editor and use this in the Your work section.

"counts"

Your task · Task 1

Using df, a cinema wants to see which genres occur most often.
Choose "scatter", "histogram", "counts" or "line".
Write the choice as a Python string.

YOUR PYTHON

Tab: indent · Shift+Tab: outdent · Esc, then Tab: leave editor

# Supplied setup — editable
import pandas as pd

data = {
    "movie": ["Moon", "River", "Spark", "Stone", "Map", "Cloud"],
    "genre": ["Drama", "Comedy", "Drama", "Action", "Comedy", "Action"],
    "minutes": [90, 105, 112, 98, 85, 120],
    "rating": [3.7, 4.2, 4.8, 4, 3.9, 4.5],
    "screen": ["One", "One", "Two", "Two", "One", "Two"],
}

df = pd.DataFrame(data)

# Your work
# Retrieve the earlier skill

Each run executes all editor code in a fresh Python session. Display a value by leaving it on the final line.

Python starts when you open a lesson.

Output

Run your code to see what Python returns.