Here's an example of graphing large values.
import matplotlib.pyplot as plt
x = [1,2,3,4,5]
y = [1000, 1002, 1001, 1003, 1005]
plt.bar(x,y)
plt.show()
The y-axis starts at 0, so the bars all look equal. I know you can use plt.ylim to manually set the limits, but is there a way for matplotlib to automatically (and smartly) set the limits to reasonable values (like 998-1008), and also perhaps show an axis break?
A little bit of simple algebra will help fix the limits:
import matplotlib.pyplot as plt
import math
x = [1,2,3,4,5]
y = [1000, 1002, 1001, 1003, 1005]
low = min(y)
high = max(y)
plt.ylim([math.ceil(low-0.5*(high-low)), math.ceil(high+0.5*(high-low))])
plt.bar(x,y)
plt.show()
In this way, you are able to find the difference between your y-values and use them to set the scale along the y-axis. I used math.ceil (as opposed to math.floor) in order to obtain the values you specified and ensure integers.
As far as an axis break goes, I'd suggest looking at this example.
A very simple way to "magnify" the top ends of the bars is to log-scale the y-axis.
plt.bar(x, y, log=True)
The yticklabels get a scientific notation as a result but it's relatively simple to return to plain formatting by formatting both major and minor ticks.
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
x = [1,2,3,4,5]
y = [1000, 1002, 1001, 1003, 1005]
# log scale
plt.bar(x, y, log=True)
# remove scientific notation
plt.gca().yaxis.set(major_formatter=ScalarFormatter(), minor_formatter=ScalarFormatter());
