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Gaining Insights with Data Visualization

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Line Plots

A line plot is a graphical representation of data that displays information along a number line. It consists of a series of points plotted on a graph, where the x-axis typically represents the independent variable, and the y-axis represents the dependent variable.

Line plots are particularly useful for displaying trends in data over time or across different categories. They are often used to visualize stock prices or weather patterns, and to compare the values of different variables, like sales volumes across various products or the performance of different sports teams. These trends or patterns can aid in making predictions about future values.

In Python, line plots can be created using the plot() function from the matplotlib.pyplot module.

Compito

Swipe to start coding

  1. Import the pyplot module of the matplotlib library with the plt alias.
  2. Generate a random array of 1000 elements (1000 x 1 array) called values using numpy.
  3. Create a single line plot based on the values array.
  4. Generate a second random array of 1000 elements called values1 using numpy.
  5. Create a second line plot based on the values1 array.

Soluzione

# Import the pyplot module
import matplotlib.pyplot as plt
import numpy as np

# Create a random array of 1000 elements
values = np.cumsum(np.random.randn(1000, 1))

# Create a line plot based on the values array
plt.plot(values)

# Create a random array of 1000 elements
values1 = np.cumsum(np.random.randn(1000, 1))

# Create a line plot based on the values1 array
plt.plot(values1);

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Sezione 1. Capitolo 3
AVAILABLE TO ULTIMATE ONLY
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