bar_chart

This function creates a bar chart.

bar_chart(**kwargs)

Input Variables

Name	Description	Type
plot_setup	Dictionary to configure the chart with the following keys: name: Path + name of the figure width: Figure width in SI units height: Figure height in SI units extension: File extension (e.g., 'png', 'svg') dots_per_inch: Resolution in dots per inch y_axis_label: Label for the y-axis x_axis_label: Label for the x-axis labels_size: Font size for labels labels_color: Color of the labels x_axis_size: Font size for x-axis labels y_axis_size: Font size for y-axis labels axises_color: Color of the axes on_grid: Grid visibility (True/False) y_log: Use logarithmic scale for y-axis (True/False) x_log: Use logarithmic scale for x-axis (True/False) colors: List of colors for the bars opacity: Opacity level of the bars	Dictionary
dataset	Data to be plotted	List or array

Output Variables

Name	Description	Type
None	The function displays the plot on the screen and saves it in the same folder as the .ipynb or .py file.	None

Example 1

Use the bar_chart function to perform a task.

# Data
df = pd.DataFrame({'x': ['2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022'],
                   'action': [15.00, 16.00, 17.00, 18.00, 19.00, 20.00, 21.00, 22.00, 23.00, 24.00],
                   'comedy': [12.00, 13.00, 14.00, 15.00, 16.00, 17.00, 18.00, 19.00, 20.00, 21.00],
                   'drama': [9.00, 10.00, 11.00, 12.00, 13.00, 14.00, 15.00, 16.00, 17.00, 18.00],
                   'horror': [8.00, 9.00, 10.00, 11.00, 12.00, 13.00, 14.00, 15.00, 16.00, 17.00],
                   'romance': [10.00, 11.00, 12.00, 13.00, 14.00, 15.00, 16.00, 17.00, 18.00, 19.00]
                  })

# Chart setup  
chart_config = {
    'name': 'figure1-4-1',
    'width': 20,
    'height': 12,
    'bar width': .10,
    'opacity': 0.7,
    'y axis label': 'Revenue (USD billion)',
    'y axis size': 14,
    'x axis label': 'Year',
    'x axis size': 14,
    'axes color': 'green',
    'labels size': 14,
    'labels color': 'blue',
    'colors': ['#E53935', '#FFB300', '#1E88E5', '#4CAF50', '#9C27B0'],
    'on grid?': True,
    'y log': False,
    'dots per inch': 600,
    'extension': 'svg',
}

# Data statement 
data = {'dataset': df}

# Call function
bar_chart(dataset=data, plot_setup=chart_config)

Figure 1. Film Revenue by Category and Year.

Notebook example