Line plots with plot() in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a simple line plot code

What will be the output of this code snippet that uses pandas to plot a line graph?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'Year': [2018, 2019, 2020, 2021], 'Sales': [250, 300, 400, 350]}
df = pd.DataFrame(data)
df.plot(x='Year', y='Sales')
plt.close()  # Prevent plot from displaying in test environment
print(type(df.plot(x='Year', y='Sales')))

A <class 'list'>

B <class 'matplotlib.axes._subplots.AxesSubplot'>

C <class 'pandas.core.frame.DataFrame'>

D <class 'matplotlib.figure.Figure'>

💡 Hint

The plot() method returns the axes object where the plot is drawn.

The pandas DataFrame plot() method returns a matplotlib AxesSubplot object representing the plot area.

❓ data_output

intermediate

Number of lines plotted with multiple columns

Given this DataFrame and plot code, how many lines will appear in the plot?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'Month': ['Jan', 'Feb', 'Mar'], 'Temp1': [30, 35, 40], 'Temp2': [25, 30, 35], 'Temp3': [20, 25, 30]}
df = pd.DataFrame(data)
df.plot(x='Month', y=['Temp1', 'Temp2', 'Temp3'])
plt.close()

A 1

B 0

C 4

D 3

💡 Hint

Each column in the y list creates one line.

Specifying multiple columns in y creates one line per column, so 3 lines appear.

❓ visualization

advanced

Effect of setting grid=true in line plots

What visual change occurs when you add grid=true to the plot() method in pandas?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'Day': [1, 2, 3, 4], 'Value': [10, 15, 7, 12]}
df = pd.DataFrame(data)
df.plot(x='Day', y='Value', grid=True)
plt.close()

A The plot lines become dashed instead of solid.

B The plot background color changes to gray.

C Grid lines appear behind the plot lines to help read values.

D The plot title is automatically added.

💡 Hint

Grid lines help to visually align points with axis ticks.

Setting grid=true adds horizontal and vertical grid lines behind the plot lines.

🔧 Debug

advanced

Identify the error in this line plot code

What error will this code raise when trying to plot?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'Date': ['2023-01-01', '2023-01-02'], 'Value': [100, 200]}
df = pd.DataFrame(data)
df.plot(x='Date', y='Value')
plt.close()

A No error, plot will display correctly.

B TypeError because 'Date' column is string, not datetime.

C ValueError because x and y columns have different lengths.

D KeyError because 'Value' column is missing.

💡 Hint

Pandas can plot string dates on x-axis without error.

Pandas can plot string dates on x-axis without error by treating them as categories.

🚀 Application

expert

Customize line plot with multiple styles

Which option correctly produces a line plot with two lines: one dashed red and one dotted blue?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'X': [1, 2, 3, 4], 'A': [10, 20, 25, 30], 'B': [15, 18, 22, 28]}
df = pd.DataFrame(data)

# Choose the correct plotting code below:

A ax = df.plot(x='X', y='A', style='r--')\ndf.plot(x='X', y='B', style='b:', ax=ax)\nplt.close() # Correct: both lines on same axes with styles

B df.plot(x='X', y='A', style='r--')\ndf.plot(x='X', y='B', style='b:')\nplt.close() # Incorrect because second plot overwrites first

C df.plot(x='X', y=['A', 'B'], style=['r--', 'b:'])\nplt.close() # Incorrect: style list must match columns exactly

D df.plot(x='X', y='A', linestyle='--', color='red')\ndf.plot(x='X', y='B', linestyle=':', color='blue')\nplt.close() # Incorrect: second plot overwrites first

💡 Hint

Use the same axes object to plot multiple lines with different styles.

Option A plots both lines on the same axes with specified styles, producing the desired plot.