Line Plot | Creating Commonly Used Plots
Ultimate Visualization with Python

Course Content

Ultimate Visualization with Python

## Ultimate Visualization with Python

1. Matplotlib Introduction
2. Creating Commonly Used Plots
3. Plots Customization
4. More Statistical Plots
5. Plotting with Seaborn

# Line Plot

Congratulations on completing the first section! Since you have already created a plot with a single point on it, it's time to create a line plot.

## Applications

Line plot is used to depict the relationship between two variables (e.g. x, y) using straight lines. More formally, it shows the relationship between continuous or ordinal variables in a continuous data point manner. Moreover, it can show how a certain variable changes with time.

## Creating a Line Plot

We'll use a function from `pyplot` that we're already familiar with to create line plots: `plot()`. Let’s have a look at an example of a line plot which shows a quadratic relationship between two variables:

In fact, this code can even be further simplified. Have a look at another example:

Here we only used one array `data_squared` for plotting. But how does `matplotlib` understand which values are used for x-axis and y-axis?

Note

If only one array (pandas `Series` object) is specified, its indices will be used for x-axis and values for y-axis.

The indices in this example are numbers from `0` to `5` including (just integer indices of a usual array of size `6`).

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

Everything was clear?

Section 2. Chapter 1

# Line Plot

Congratulations on completing the first section! Since you have already created a plot with a single point on it, it's time to create a line plot.

## Applications

Line plot is used to depict the relationship between two variables (e.g. x, y) using straight lines. More formally, it shows the relationship between continuous or ordinal variables in a continuous data point manner. Moreover, it can show how a certain variable changes with time.

## Creating a Line Plot

We'll use a function from `pyplot` that we're already familiar with to create line plots: `plot()`. Let’s have a look at an example of a line plot which shows a quadratic relationship between two variables:

In fact, this code can even be further simplified. Have a look at another example:

Here we only used one array `data_squared` for plotting. But how does `matplotlib` understand which values are used for x-axis and y-axis?

Note

If only one array (pandas `Series` object) is specified, its indices will be used for x-axis and values for y-axis.

The indices in this example are numbers from `0` to `5` including (just integer indices of a usual array of size `6`).

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

Everything was clear?

Section 2. Chapter 1

# Line Plot

Congratulations on completing the first section! Since you have already created a plot with a single point on it, it's time to create a line plot.

## Applications

Line plot is used to depict the relationship between two variables (e.g. x, y) using straight lines. More formally, it shows the relationship between continuous or ordinal variables in a continuous data point manner. Moreover, it can show how a certain variable changes with time.

## Creating a Line Plot

We'll use a function from `pyplot` that we're already familiar with to create line plots: `plot()`. Let’s have a look at an example of a line plot which shows a quadratic relationship between two variables:

In fact, this code can even be further simplified. Have a look at another example:

Here we only used one array `data_squared` for plotting. But how does `matplotlib` understand which values are used for x-axis and y-axis?

Note

If only one array (pandas `Series` object) is specified, its indices will be used for x-axis and values for y-axis.

The indices in this example are numbers from `0` to `5` including (just integer indices of a usual array of size `6`).

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

1. Use the correct function for creating a line plot.
2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.

Everything was clear?

Congratulations on completing the first section! Since you have already created a plot with a single point on it, it's time to create a line plot.

## Applications

Line plot is used to depict the relationship between two variables (e.g. x, y) using straight lines. More formally, it shows the relationship between continuous or ordinal variables in a continuous data point manner. Moreover, it can show how a certain variable changes with time.

## Creating a Line Plot

We'll use a function from `pyplot` that we're already familiar with to create line plots: `plot()`. Let’s have a look at an example of a line plot which shows a quadratic relationship between two variables:

In fact, this code can even be further simplified. Have a look at another example:

Here we only used one array `data_squared` for plotting. But how does `matplotlib` understand which values are used for x-axis and y-axis?

Note

If only one array (pandas `Series` object) is specified, its indices will be used for x-axis and values for y-axis.

The indices in this example are numbers from `0` to `5` including (just integer indices of a usual array of size `6`).

2. Pass in the correct order `x_data` (x-axis) and `y_data` (y-axis) as the first two arguments.
3. Pass the rightmost argument such that the plot will have `'o'` markers and dashed lines.