CODEWITHSUNDEEP
pythonmatplotlibdata-visualization
Caitlin Garcia
Caitlin Garcia

Reputation: 1

How to scale and customize axis range in matplotlib?

I am new to data visualization, so please bear with me. I am trying to create a data plot that describes various different attributes on a data set on blockbuster movies. The x-axis will be year of the movie and the y-axis will be worldwide gross. Now, some movies have made upwards of a billion in this category, and it seems that my y axis is overwhelmed as it completely blocks out the numbers and becomes illegible. Here is what I have thus far:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv('blockbusters.csv')
fig, ax = plt.subplots()
ax.set_title('Top Grossing Films')
ax.set_xlabel('Year')
ax.set_ylabel('Worldwide Grossing')

x = df['year'] #xaxis
y = df['worldwide_gross'] #yaxis

plt.show()

Any tips on how to scale this down? Ideally it could be presented on a scale of 10. Thanks in advance!

Upvotes: 0

Views: 305

Answers (1)

Arco Bast
Arco Bast

Reputation: 3892

You could try logarithmic scaling:

ax.set_yscale('log')

You might want to manually set the ticks on the y-axis using

ax.set_yticks([list of values for which you want to have a tick])
ax.set_yticklabels([list of labels you want on each tick]) # optional

Another way to approach this might be to rank the movies (which gross is the highest, second highest, ...), i.e. on the y axis you would plot

df['worldwide_gross'].rank()

Edit: as you indicate, one might also check the dtypes to make sure the data is numerical. If not, use .astype(int) or .astype(float) to convert it.

Upvotes: 1

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