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Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

The ** matplotlib** Python library, developed by John Hunter and many other contributors, is used to create high-quality graphs, charts, and figures. The library is extensive and capable of changing very minute details of a figure. Some basic concepts and functions provided in

`matplotlib`

are:The entire illustration is called a figure and each plot on it is an axes (do not confuse *Axes* with *Axis*). The figure can be thought of as a canvas on which several plots can be drawn. We obtain the figure and the axes using the subplots() function:

import matplotlib.pyplot as plt fig, ax = plt.subplots()

The very first thing required to plot a graph is data. A dictionary of key-value pairs can be declared, with keys and values as the `x`

and `y`

values. After that, `scatter()`

, `bar()`

, and `pie()`

, along with tons of other functions, can be used to create the plot:

# Create data: data = { "France": 65.4, "Germany": 82.4, "Italy": 59.2, "UK": 66.9 } # Use keys and values as x and y axis values: x_axis_data = data.keys() y_axis_data = data.values() # Plotting a bar graph: ax.bar(x_axis_data, y_axis_data)

The figure and axes obtained using `subplots()`

can be used for modification. Properties of the x-axis and y-axis (labels, minimum and maximum values, etc.) can be changed using `Axes.set()`

:

# Setting properties of axes: ax.set(ylim=[0, 100], ylabel='Population (in million)', xlabel='Country', title='European Countries by Population')

Lastly, `pyplot.show()`

is used to display the graph.

The following code demonstrates all of the points discussed above:

import matplotlib.pyplot as plt fig, ax = plt.subplots() # Create data: data = { "France": 65.4, "Germany": 82.4, "Italy": 59.2, "UK": 66.9 } # Use keys and values as x and y axis values: x_axis_data = data.keys() y_axis_data = data.values() # Plotting a bar graph: ax.bar(x_axis_data, y_axis_data) # Setting properties of axes: ax.set(ylim=[0, 100], ylabel='Population (in million)', xlabel='Country', title='European Countries by Population') # Displaying the graph: plt.show()

RELATED TAGS

matplotlib

python

graph

figure

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Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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