Scatter Plot components in matplotlib
- A scatter plot in Matplotlib is a type of plot that displays individual data points on a two-dimensional graph.
- Each point on the graph represents a single observation.
- Components of a scatter plot in matplotlib:
1. Figure and
Axes:
- Figure (`plt.figure()`): The
top-level container for the entire plot.
- Axes (`plt.subplot()` or
`plt.subplots()`):
The area within the figure where the data points are plotted.
2. Data Plotting:
- Scatter Plot (`plt. scatter()`):
This is the main function for creating scatter plots. It allows you to specify
the x and y coordinates of each point, along with various visual properties.
plt.scatter(x, y, label='Data Points',
color='red', marker='o', s=50)
- `x` and `y`: The data to be plotted along
the x and y axes.
- `label`: A label for the data series.
- `Color`: The color of the markers.
- `marker`: The marker style (e.g., 'o' for
circles).
- `s`: The size of the markers.
3. Title and
Labels:
- Title (`plt. title()`): Adds a title to
the plot.
plt.title('Scatter Plot')
- Axis Labels (`plt.xlabel()` and
`plt.ylabel()`): Adds labels to the x and y axes.
plt.xlabel('x')
plt.ylabel('y')
4. Legend:
- - Legend (`plt.legend()`): Displays a legend that describes the elements in the plot.
- The `label` parameter in the plotting function is used to associate a label with each data series.
plt.legend()
5. Grid Lines:
- Grid (`plt.grid()`): Adds grid
lines to the plot.
plt.grid(True)
6. Customizing
Marker Appearance:
- Color (`color`): Specifies the
color of the markers.
- Marker (`marker`): Specifies the
marker style for data points.
- Markersize (`s`): Sets the size of
markers.
These properties are specified in the
`plt.scatter()` function.
7. Saving and
Displaying the Plot:
- Save (`plt.savefig()`): Saves the
plot to a file.
- Show (`plt.show()`): Displays the plot
on the screen.
plt.show()
example:- a
scatter plot with these components:
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(42)
x =
np.random.rand(50)
y = 2 * x + 1 +
0.1 * np.random.randn(50)
plt.figure(figsize=(8,
4))
plt.scatter(x, y,
label='Data Points', color='red', marker='o', s=50)
plt.title('Scatter
Plot')
plt.xlabel('x')
plt.ylabel('y')
plt.legend()
plt.grid(True)
plt.show()
0 Comments