DATA VISUALISATION

WHAT IS IN THIS SECTION

This section covers presenting data in a user friendly format such as charts and graphs and covers manipulating and gathering data for analysis.

VIDEOS IN THIS SECTION

A Quick guide to creating line graphs

A quick guide to creating bar charts

A quick guide to creating pie charts

CLICK TO EXPAND SECTION ​👇

CREATE A LINE GRAPH

• LEARN
• VIDEO
• TASK

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Using the matplotlib import to create a quick and easy to code line graph to represent your data.

from matplotlib import pyplot as plt

x_axis = ["Mac","PC","Google Home","Playstation","C64","GoPro","Samsung","iphone","Huawei","X-Box"]
y_axis = [21,45,35,76,34,87,34,5,60,50]

plt.plot(x_axis,y_axis)

plt.title("Technology Review")
plt.xlabel("Tech Type")
plt.ylabel("User Rating")

plt.show()

CREATE A BAR CHART

• LEARN
• VIDEO
• TASK

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Using the same principle as above but this time creating a vertical bar chart and a horizontal bar chart. This method also uses numpy as a method of arranging the tech array. As can be seen from the video the difference between the vertical and horizontal is plt.barh VS plt.barv.

CREATE A PIE CHART

GATHERING DATA

This section will look at methods of gathering data, producing statistics and preparing data for presenting.

OTHER USEFUL WEBSITES

MATPLOTLIB     Official Matplotlib site with loads of methods you can use with this library.
DATA TO FISH     A good website with data analysis guidance for libraries such as numpy, matplotlit and pandas