To plot numerical values in matplotlib, you need to first import the matplotlib library in your python script. Then, you can create a figure and axis object using the plt.subplots() function. Next, you can use the plot() function to plot your numerical values on the axis. You can customize the plot by adding labels, titles, legends, and changing the plot style and color. Finally, you can display the plot by calling the plt.show() function.

## What is the default size of a matplotlib plot?

The default size of a matplotlib plot is 6.4 by 4.8 inches.

## How to plot numerical values in matplotlib using a line plot?

To plot numerical values in matplotlib using a line plot, you can follow these steps:

- Import the necessary libraries:

```
1
``` |
```
import matplotlib.pyplot as plt
``` |

- Define your numerical values as lists or arrays:

1 2 |
x_values = [1, 2, 3, 4, 5] y_values = [10, 12, 15, 18, 20] |

- Create a line plot using the plot function:

```
1
``` |
```
plt.plot(x_values, y_values)
``` |

- Add labels to the plot:

1 2 3 |
plt.xlabel('X values') plt.ylabel('Y values') plt.title('Line Plot of Numerical Values') |

- Display the plot:

```
1
``` |
```
plt.show()
``` |

This will create a line plot of the numerical values specified in `x_values`

and `y_values`

with the x-axis labeled as 'X values', the y-axis labeled as 'Y values', and the plot titled as 'Line Plot of Numerical Values'.

## How to add data labels to a plot in matplotlib?

To add data labels to a plot in matplotlib, you can use the `annotate`

function in matplotlib.

Here is an example code snippet:

1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [10, 20, 15, 25, 30] # Create a plot plt.plot(x, y) # Add data labels for i, txt in enumerate(y): plt.annotate(txt, (x[i], y[i]), textcoords="offset points", xytext=(0,10), ha='center') plt.show() |

In this code, we first create a plot using `plt.plot`

. Then, we loop through the data points and use the `annotate`

function to add data labels to each point. The `textcoords`

argument specifies that the text is offset by 10 points from the data point, and the `ha`

argument specifies that the text should be centered horizontally.

You can customize the appearance of the data labels by adjusting the arguments in the `annotate`

function.