How to Prevent Numbers Being Changed to Exponential Form in Python Matplotlib Figure

How to prevent numbers being changed to exponential form in a plot

The formatting of tick labels is controlled by a Formatter object, which assuming you haven't done anything fancy will be a ScalerFormatterby default. This formatter will use a constant shift if the fractional change of the values visible is very small. To avoid this, simply turn it off:

plt.plot(arange(0,100,10) + 1000, arange(0,100,10))
ax = plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.draw()

If you want to avoid scientific notation in general,

ax.get_xaxis().get_major_formatter().set_scientific(False)

Can control this with globally via the axes.formatter.useoffset rcparam.

Prevent scientific notation

In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.

However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).

For example:

fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()

If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').

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Difference between "offset" and "scientific notation"

In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.

Consider this example:

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)

fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()

The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).

We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).

For example, if we call:

ax.ticklabel_format(style='plain')

We'll disable the scientific notation on the y-axis:

And if we call

ax.ticklabel_format(useOffset=False)

We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:

Finally, we can disable both through:

ax.ticklabel_format(useOffset=False, style='plain')

How to prevent 1e9 from being shown to exponential form in Python matplotlib figure

My thanks to ImportanceOfBeingErnest above, as

a.yaxis.offsetText.set_visible(False)

solves.

How to remove scientific notation on a matplotlib log-log plot

Those are minor ticks on the x-axis (i.e. they are not on integer powers of 10), not major ticks. matplotlib automatically detemines if it should label the major or minor ticks - in this case because you don't have any major ticks displayed in the x range, the minor ticks are being labelled). So, you need to use the set_minor_formatter method:

ax.xaxis.set_minor_formatter(mticker.ScalarFormatter())

The reason it works on the y-axis is because those ticks are major ticks (i.e. on integer powers of 10), not minor ticks.

Changing yaxis number format in matplotlib

I have found this documentation inside the matplotlib site https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.ticklabel_format.html. I suppose you need to set the second attribute to plain.

Matplotlib: setting the Y-axis to none scientific notation AFTER changing the Y-axis to log scale

As explained, here you can set a ScalarFormatter to leave out scientific notation. .set_scientific(False) would be needed to also suppress the scientific notation for large numbers.

You might need axs.yaxis.set_major_formatter(ticker.FuncFormatter(lambda y, _: '{:g}'.format(y))) if you're dealing with negative powers.

from matplotlib import pyplot as plt
from matplotlib.ticker import ScalarFormatter

fig = plt.figure(figsize=(30, 15))
axs = fig.add_subplot(1, 1, 1)
axs.plot()
axs.set_ylim(100000, 100000000)
axs.set_yscale('log')
formatter = ScalarFormatter()
formatter.set_scientific(False)
axs.yaxis.set_major_formatter(formatter)
plt.show()

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