Line plots with plot() in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a line plot of the 'sales' column from the DataFrame.

Pandas

df.[1](y='sales')

Drag options to blanks, or click blank then click option'

Ahist

Bplot

Cshow

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'show' instead of 'plot' which does not exist on DataFrame.

Using 'scatter' which creates scatter plots, not line plots.

Using 'hist' which creates histograms, not line plots.

The plot method creates a line plot by default when given a column name.

2fill in blank

medium

Complete the code to plot the 'temperature' column with a red line.

Pandas

df.plot(y='temperature', color='[1]')

Drag options to blanks, or click blank then click option'

Agreen

Bblue

Cred

Dyellow

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a color other than red when the instruction asks for red.

Using color names that are not recognized by matplotlib.

The color parameter sets the line color. 'red' makes the line red.

3fill in blank

hard

Fix the error in the code to plot the 'profit' column as a line plot.

Pandas

df.[1](y='profit')

Drag options to blanks, or click blank then click option'

Aplot

Bshow

Cdraw

Dline

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'show' which is a pyplot function, not a DataFrame method.

Using 'draw' or 'line' which are not valid DataFrame methods.

The correct method to create line plots from a DataFrame is plot.

4fill in blank

hard

Fill both blanks to create a line plot of 'revenue' with a dashed green line.

Pandas

df.plot(y='[1]', linestyle='[2]', color='green')

Drag options to blanks, or click blank then click option'

Arevenue

Bsales

C--

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name for 'y'.

Using a solid line '-' instead of dashed '--'.

The 'y' parameter should be 'revenue' to plot that column. The 'linestyle' '--' creates a dashed line. The color is set to green.

5fill in blank

hard

Fill both blanks to plot 'expenses' with a blue dotted line and label the plot 'Expenses Over Time'.

Pandas

df.plot(y='[1]', color='[2]', linestyle=':', title='Expenses Over Time')

Drag options to blanks, or click blank then click option'

Aexpenses

Bblue

C:

Dprofit

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name like 'profit'.

Using solid or dashed lines instead of dotted.

Choosing a color other than blue.

Plot the 'expenses' column with blue color and dotted linestyle ':' to match the instructions.

Practice

1. What does the plot() function in pandas primarily create?

easy

A. A list of column names

B. A table of data values

C. A summary statistics report

D. A line plot to show data trends over an axis

Solution

1. Step 1: Understand the purpose of plot() in pandas

   The plot() function is used to create visual graphs from data, most commonly line plots.

2. Step 2: Identify the type of plot created

   By default, DataFrame.plot() creates a line plot to show how data changes over an ordered axis like time.

3. Final Answer:

   A line plot to show data trends over an axis -> Option D

4. Quick Check:

   plot() = line plot [OK]

Hint: plot() makes line plots by default to show trends [OK]

Common Mistakes:

• Thinking plot() creates tables
• Confusing plot() with summary functions
• Assuming plot() lists columns

2. Which of the following is the correct syntax to plot the column 'Sales' from a DataFrame df using the y parameter?

easy

A. df.plot('Sales')

B. df.plot(y='Sales')

C. df.plot(column='Sales')

D. df.plot(x='Sales')

Solution

1. Step 1: Recall the parameter to select columns in plot()

   The y parameter specifies which column(s) to plot on the y-axis.

2. Step 2: Match the correct syntax

   Using df.plot(y='Sales') correctly tells pandas to plot the 'Sales' column as the y-axis data.

3. Final Answer:

   df.plot(y='Sales') -> Option B

4. Quick Check:

   Use y='column' to plot that column [OK]

Hint: Use y='column' to plot that column in plot() [OK]

Common Mistakes:

• Using 'column' instead of 'y' parameter
• Passing column name without parameter
• Using x='Sales' to plot y-axis

3. Given the code:

import pandas as pd
import matplotlib.pyplot as plt

data = {'Month': ['Jan', 'Feb', 'Mar'], 'Sales': [100, 150, 120]}
df = pd.DataFrame(data)
df.plot(x='Month', y='Sales')
plt.show()

What will the plot show?

medium

A. A scatter plot of sales vs months

B. A bar plot with sales on x-axis and months on y-axis

C. A line plot with months on x-axis and sales on y-axis

D. An error because 'Month' is not numeric

Solution

1. Step 1: Understand the plot parameters

   The code uses x='Month' and y='Sales' to plot sales against months.

2. Step 2: Recognize default plot type

   By default, plot() creates a line plot, even if x-axis is categorical like months.

3. Final Answer:

   A line plot with months on x-axis and sales on y-axis -> Option C

4. Quick Check:

   plot(x=cat, y=num) = line plot [OK]

Hint: plot() defaults to line plot even with categorical x-axis [OK]

Common Mistakes:

• Expecting bar or scatter plot by default
• Thinking non-numeric x causes error
• Confusing axis labels

4. What is wrong with this code snippet?

df = pd.DataFrame({'A': [1, 2, 3]})
df.plot('A')

medium

A. It will plot column 'A' on y-axis but x-axis will be default index

B. It will cause a syntax error because 'y' parameter is missing

C. It will raise a runtime error because 'A' is not specified as y

D. It will plot column 'A' on x-axis instead of y-axis

Solution

1. Step 1: Analyze the plot() call with one positional string argument

   When a string is passed positionally to plot(), it specifies the column for the y-axis.

2. Step 2: Understand default x-axis behavior

   Since no x parameter is specified, the x-axis uses the DataFrame's index.

3. Final Answer:

   It will plot column 'A' on y-axis but x-axis will be default index -> Option A

4. Quick Check:

   plot('A') = y='A' vs index [OK]

Hint: plot('col') sets y='col' vs index; specify x/y to control [OK]

Common Mistakes:

• Assuming 'A' is x-axis without specifying
• Expecting syntax or runtime error
• Confusing x and y parameters

5. You have a DataFrame df with columns 'Date', 'Temperature', and 'Humidity'. You want to plot both 'Temperature' and 'Humidity' over 'Date' on the same line plot with a title 'Weather Data'. Which code correctly does this?

hard

A. df.plot(x='Date', y=['Temperature', 'Humidity'], title='Weather Data')

B. df.plot(y=['Temperature', 'Humidity'], x='Date', label='Weather Data')

C. df.plot(x='Date', y='Temperature', 'Humidity', title='Weather Data')

D. df.plot(x='Date', y=['Temperature', 'Humidity']).title('Weather Data')

Solution

1. Step 1: Select multiple columns for y-axis correctly

   Use a list for the y parameter: y=['Temperature', 'Humidity'].

2. Step 2: Add title properly in plot()

   The title parameter inside plot() sets the plot title directly.

3. Step 3: Verify syntax correctness

   df.plot(x='Date', y=['Temperature', 'Humidity'], title='Weather Data') uses correct syntax with x, y as list, and title parameter all in one call.

4. Final Answer:

   df.plot(x='Date', y=['Temperature', 'Humidity'], title='Weather Data') -> Option A

5. Quick Check:

   Use y=[cols], x=col, title='text' in plot() [OK]

Hint: Use y=[cols], x=col, title='text' inside plot() [OK]

Common Mistakes:

• Passing multiple y columns without list
• Using label instead of title for plot title
• Using .title() instead of .set_title()