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
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A Quick guide to creating line graphs
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A quick guide to creating bar charts
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A quick guide to creating pie charts
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CLICK TO EXPAND SECTION 👇
CREATE A LINE GRAPH
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
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
DATA TO FISH A good website with data analysis guidance for libraries such as numpy, matplotlit and pandas
