Зміст курсу

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

Plots Decoration

Setting Style

First, let’s start with setting the style for the plot. seaborn has a set_style() function exactly for this purpose. We are interested in its only required parameter called style. It has several possible values, which are all different styles:

'white';
'dark';
'whitegrid';
'darkgrid';
'ticks'.

Feel free to experiment with them:


              1234567
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Palette

Another option you have is to change the colors of the plot elements in seaborn using the set_palette() function. We'll focus on its only required parameter palette. Here are a few possible palettes:

Circular palettes: 'hls', 'husl';
Perceptually uniform palettes: 'rocket', 'magma', 'mako', etc;
Diverging color palettes: 'RdBu', 'PRGn', etc;
Sequential color palettes: 'Greys', 'Blues', etc.

You can explore more of them here. Once again, feel free to experiment with different palettes:


              12345678910
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Context

There is another function in the seaborn library, set_context(). It affects such aspects as the size of the labels, lines, and other elements of the plot (the overall style is not affected).

Its most important parameter context which can either be a dictionary (dict) of parameters or a name of a preconfigured set (string type).

'notebook' is the default context, other contexts are 'paper', 'talk', and 'poster', which are essentially just versions of the notebook parameters scaled by a certain value.

Here is an example, you can try different contexts and see the difference:


              123456789101112
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Setting the context
sns.set_context('paper')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

You can explore more about set_context() in its documentation.

Завдання

Use the correct function to set the style to 'dark'.
Use the correct function to set the palette to 'rocket'.
Use the correct function to set the context to 'talk'.

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 5. Розділ 3

Plots Decoration

Setting Style

'white';
'dark';
'whitegrid';
'darkgrid';
'ticks'.

Feel free to experiment with them:


              1234567
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Palette

Circular palettes: 'hls', 'husl';
Perceptually uniform palettes: 'rocket', 'magma', 'mako', etc;
Diverging color palettes: 'RdBu', 'PRGn', etc;
Sequential color palettes: 'Greys', 'Blues', etc.

You can explore more of them here. Once again, feel free to experiment with different palettes:


              12345678910
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Context

Its most important parameter context which can either be a dictionary (dict) of parameters or a name of a preconfigured set (string type).

'notebook' is the default context, other contexts are 'paper', 'talk', and 'poster', which are essentially just versions of the notebook parameters scaled by a certain value.

Here is an example, you can try different contexts and see the difference:


              123456789101112
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Setting the context
sns.set_context('paper')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

You can explore more about set_context() in its documentation.

Завдання

Use the correct function to set the style to 'dark'.
Use the correct function to set the palette to 'rocket'.
Use the correct function to set the context to 'talk'.

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 5. Розділ 3

Plots Decoration

Setting Style

'white';
'dark';
'whitegrid';
'darkgrid';
'ticks'.

Feel free to experiment with them:


              1234567
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Palette

Circular palettes: 'hls', 'husl';
Perceptually uniform palettes: 'rocket', 'magma', 'mako', etc;
Diverging color palettes: 'RdBu', 'PRGn', etc;
Sequential color palettes: 'Greys', 'Blues', etc.

You can explore more of them here. Once again, feel free to experiment with different palettes:


              12345678910
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Context

Its most important parameter context which can either be a dictionary (dict) of parameters or a name of a preconfigured set (string type).

'notebook' is the default context, other contexts are 'paper', 'talk', and 'poster', which are essentially just versions of the notebook parameters scaled by a certain value.

Here is an example, you can try different contexts and see the difference:


              123456789101112
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Setting the context
sns.set_context('paper')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

You can explore more about set_context() in its documentation.

Завдання

Use the correct function to set the style to 'dark'.
Use the correct function to set the palette to 'rocket'.
Use the correct function to set the context to 'talk'.

Все було зрозуміло?

Дякуємо за ваш відгук!

Setting Style

'white';
'dark';
'whitegrid';
'darkgrid';
'ticks'.

Feel free to experiment with them:


              1234567
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Palette

Circular palettes: 'hls', 'husl';
Perceptually uniform palettes: 'rocket', 'magma', 'mako', etc;
Diverging color palettes: 'RdBu', 'PRGn', etc;
Sequential color palettes: 'Greys', 'Blues', etc.

You can explore more of them here. Once again, feel free to experiment with different palettes:


              12345678910
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

Setting Context

Its most important parameter context which can either be a dictionary (dict) of parameters or a name of a preconfigured set (string type).

'notebook' is the default context, other contexts are 'paper', 'talk', and 'poster', which are essentially just versions of the notebook parameters scaled by a certain value.

Here is an example, you can try different contexts and see the difference:


              123456789101112
            
import seaborn as sns
import matplotlib.pyplot as plt
# Setting the style
sns.set_style('darkgrid')
# Setting the palette
sns.set_palette('magma')
# Setting the context
sns.set_context('paper')
# Loading a built-in dataset of the Titanic passengers
titanic_df = sns.load_dataset('titanic')
sns.countplot(data=titanic_df, x='class')
plt.show()

You can explore more about set_context() in its documentation.

Завдання

Use the correct function to set the style to 'dark'.
Use the correct function to set the palette to 'rocket'.
Use the correct function to set the context to 'talk'.

Секція 5. Розділ 3