Conteúdo do Curso

Ultimate Visualization with Python

1. Matplotlib Introduction

Plotting Applications Why Use Matplotlib?Creating a Canvas Basic Plotting

2. Creating Commonly Used Plots

Line Plot Multiple Line Plots Scatter Plot Bar Chart Stacked Bar Charts Grouped Bar Charts

3. Plots Customization

Adding Title to the Plot Adding Legend Axes Customization Colors and Transparency Customizing Grid Subplots

4. More Statistical Plots

Histogram Box Plot Pie Chart

5. Plotting with Seaborn

Seaborn Introduction Countplot Plots Decoration KDE Plot Joint Plot Pair Plot Heatmap

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:


              1234567
            
import matplotlib.pyplot as plt
import numpy as np
data_linear = np.arange(0, 6)
data_squared = data_linear ** 2
# Creating a line plot with specifying x and y
plt.plot(data_linear, data_squared, '-o')
plt.show()

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


              123456
            
import matplotlib.pyplot as plt
import numpy as np
data_squared = np.arange(0, 6) ** 2
# Creating a line plot using only one array
plt.plot(data_squared, '-o')
plt.show()

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).

Tarefa

Swipe to show code editor

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Obrigado pelo seu feedback!

Seção 2. Capítulo 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

Creating a Line Plot


              1234567
            
import matplotlib.pyplot as plt
import numpy as np
data_linear = np.arange(0, 6)
data_squared = data_linear ** 2
# Creating a line plot with specifying x and y
plt.plot(data_linear, data_squared, '-o')
plt.show()

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


              123456
            
import matplotlib.pyplot as plt
import numpy as np
data_squared = np.arange(0, 6) ** 2
# Creating a line plot using only one array
plt.plot(data_squared, '-o')
plt.show()

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).

Tarefa

Swipe to show code editor

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Obrigado pelo seu feedback!

Seção 2. Capítulo 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

Creating a Line Plot


              1234567
            
import matplotlib.pyplot as plt
import numpy as np
data_linear = np.arange(0, 6)
data_squared = data_linear ** 2
# Creating a line plot with specifying x and y
plt.plot(data_linear, data_squared, '-o')
plt.show()

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


              123456
            
import matplotlib.pyplot as plt
import numpy as np
data_squared = np.arange(0, 6) ** 2
# Creating a line plot using only one array
plt.plot(data_squared, '-o')
plt.show()

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).

Tarefa

Swipe to show code editor

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Obrigado pelo seu feedback!

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

Creating a Line Plot


              1234567
            
import matplotlib.pyplot as plt
import numpy as np
data_linear = np.arange(0, 6)
data_squared = data_linear ** 2
# Creating a line plot with specifying x and y
plt.plot(data_linear, data_squared, '-o')
plt.show()

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


              123456
            
import matplotlib.pyplot as plt
import numpy as np
data_squared = np.arange(0, 6) ** 2
# Creating a line plot using only one array
plt.plot(data_squared, '-o')
plt.show()

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).

Tarefa

Swipe to show code editor

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Seção 2. Capítulo 1

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo