Course Content

Ultimate Visualization with Python

## Ultimate Visualization with Python

# 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`

).

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Everything was clear?

# 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`

).

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Everything was clear?

# 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`

).

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.

Everything was clear?

## 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

`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:

`data_squared`

for plotting. But how does `matplotlib`

understand which values are used for x-axis and y-axis?

Note

`Series`

object) is specified, its indices will be used for x-axis and values for y-axis.

`0`

to `5`

including (just integer indices of a usual array of size `6`

).

Task

- Use the correct function for creating a line plot.
- Pass in the correct order
`x_data`

(x-axis) and`y_data`

(y-axis) as the first two arguments. - Pass the rightmost argument such that the plot will have
`'o'`

markers and dashed lines.