Matplotlib: Format Axis Offset-Values to Whole Numbers or Specific Number

Change y-axis offset value in matplotlib

I'm not going to claim I came up with this one, but:

import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter, FormatStrFormatter

class FixedOrderFormatter(ScalarFormatter):
    """Formats axis ticks using scientific notation with a constant order of 
    magnitude"""
    def __init__(self, order_of_mag=0, useOffset=True, useMathText=False):
        self._order_of_mag = order_of_mag
        ScalarFormatter.__init__(self, useOffset=useOffset, 
                                 useMathText=useMathText)
    def _set_orderOfMagnitude(self, range):
        """Over-riding this to avoid having orderOfMagnitude reset elsewhere"""
        self.orderOfMagnitude = self._order_of_mag

# Create example df
df = pd.DataFrame({
    'date': ['2017-01-01', '2017-02-01', '2017-03-01', '2017-04-01'],
    'Actual': [10250000000, 10350000000, 10400000000, 10380000000],
    'Forecast': [9000000000, 10315000000, 10410000000, 10400000000]
})

#Plot df
plt.rcParams["figure.figsize"] = (14, 8)
fig = plt.figure()
ax  = fig.add_subplot(111)
ax.plot(df.date, df['Actual'], c='black', label='Actual', linewidth=3.0)
ax.plot(df.date, df['Forecast'], c='blue', label='Forecast')
leg = plt.legend()

# set the desired exponent using the FixedOrderFormatter class defined above
ax.yaxis.set_major_formatter(FixedOrderFormatter(9))

plt.show()

output:

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')

Specify format of floats for tick labels

See the relevant documentation in general and specifically

from matplotlib.ticker import FormatStrFormatter

fig, ax = plt.subplots()

ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))

Matplotlib: cancelling the offset of axis introduced in matplotlib 2.0

In matplotlib v2.0.x, the default axes margin has changed, from 0 to 0.05, which is the value controlling the whitespace around your data on the axes. See here for more on the reasoning behind this change.

There are several ways to revert to the previous behaviour.

1) To reset margins to 0 for a single Axes instance:

plt.margins(0)

or

ax.margins(0)

2) To reset margins to 0 for all plots in a script, use rcParams and set this at the top of your script:

plt.rcParams['axes.autolimit_mode'] = 'round_numbers'
plt.rcParams['axes.xmargin'] = 0.
plt.rcParams['axes.ymargin'] = 0.

3) To change the default value for all plots on a machine, modify your the matplotlibrc file to include these lines:

axes.autolimit_mode: round_numbers
axes.xmargin        : 0.
axes.ymargin        : 0.

Note that to use method (1) and truly get the old behaviour, you may also need to set plt.rcParams['axes.autolimit_mode'] = 'round_numbers'.

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