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Gaining Insights with Data Visualization

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Scatter Plots

A scatter plot is a type of graph that used to display values for typically two variables for a set of data. Each value in the dataset is represented by a dot or mark on the plot, positioned according to its values for the variables.

Scatter plots are particularly useful for showing relationships between two continuous variables. They can be used to visualize patterns and trends in data and to identify correlations between variables.

For instance, a scatter plot could illustrate the relationship between a person's height and weight or track changes in a company's stock price over time. Additionally, enhancements like color coding or different marker styles can further elucidate the relationships among multiple variables or categories.

Oppgave

Swipe to start coding

  1. Import the pandas library with the pd alias.
  2. Initialize a pandas DataFrame with 100 records, setting the 'x_values' column to range from 1 to 101 exclusive.
  3. Create a scatter plot with the 'x_values' column on the x-axis and the 'y_values' column on the y-axis.
  4. Set the title of the graph to 'Scatter Plot'.

Løsning

import matplotlib.pyplot as plt
import numpy as np
# Import the pandas library
import pandas as pd

# Create a DataFrame
df = pd.DataFrame({'x_values': range(1, 101), 'y_values': np.random.randn(100) * 15 + range(1, 101)})

# Create a scatter plot
plt.scatter('x_values', 'y_values', data=df)

# Set the title of the graph
plt.title('Scatter plot')
plt.show()

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