The matplotlib ticker FuncFormatter

Question

I am trying to manually set the ticker for a bar plot. I am using the FunFormatter function. Yet, I found that the behavior of the FunFormmater is too strange. For X-axis range from 0 to 91, I found that the FunFormmater returns the following ... Any idea how does it work. Here is the link for the data file Thanks in advance

-10.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 28.805725806451605 38.374395161290316 41.22463709677419 47.128709677419344 48.55383064516128 49.36818548387095 51.20048387096774 52.42201612903225 53.439959677419345 53.439959677419345 53.03278225806451 53.643548387096764 56.08661290322579 59.75120967741935 64.63733870967741 70.54141129032257 76.85266129032257 83.16391129032257 95.58282258064514

import numpy as np
import matplotlib.pyplot as plt
import pandas as p
import matplotlib.mlab as m
import matplotlib
import matplotlib.ticker as ticker

file1=np.load('numofdays.npz')
fig,axes=plt.subplots(ncols=1)
ax=axes
x=np.arange(len(file1['arr_0']))
y=np.array(file1['arr_0'])
ax.bar(x,y)
mydates=p.DatetimeIndex(file1['arr_1'])

def mme(xx,pos=None):
    print(xx)
#    print(mydates[int(xx-9)].strftime('%Y-%m-%d'))
    return mydates[int(xx-9)].strftime('%Y-%m-%d')

ax.xaxis.set_major_locator(ticker.MultipleLocator(10))
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mme))
fig.autofmt_xdate()

What is strange about those numbers? Note that you have a lot more information than we have, e.g. access to the data, an idea about the desired outcome etc. See minimal reproducible example for what is needed to help here. From the information provided until now, one can deduce that you have a dataset of around 100 rows and hence the Formatter will format some numbers in the range 0 to 100. This seems reasonable. — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Oct 20, 2018 at 3:23
Thanks for your comment. I attached the data file. Any idea why those number starts with -10. Also, the script doesn't work if I replace the int(xx-9) with int(xx) on the mme function. — Kernel
– Kernel, Commented Oct 20, 2018 at 3:28
I suppose the first (invisible) tick on the axis is at -10. Can you also say what exactly you are trying to achieve? In your own words, how should the axis look like at the end? — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Oct 20, 2018 at 3:33
My data is grided on uneven time, so I am trying to set my time manually. That is why I am using FuncFormatter function. I expected that I will see my time x-axis starts at the first time which is 1982-01-02, yet it starts at 2006-01-04. Also, the last point is at 2011-12-21, yet I found that the last data is at 2009-04-02. — Kernel
– Kernel, Commented Oct 20, 2018 at 3:39

ImportanceOfBeingErnest · Accepted Answer · 2018-10-20 04:02:00Z

It's a bit dangerous to show only every tenth label for unequally spaced data, because you don't know what happens in between.

However to get your script running, you will of course need to make sure the position xx is a valid index of the array. E.g. the position 100 is not valid, because your array only has 92 elements. To this end you may just introduce a condition.

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

import matplotlib.ticker as ticker

file1=np.load('data/numofdays.npz')

fig,ax=plt.subplots(ncols=1)

x=np.arange(len(file1['arr_0']))
y=np.array(file1['arr_0'])
ax.bar(x,y)
mydates=p.DatetimeIndex(file1['arr_1'])

def mme(xx,pos=None):
    if int(xx) in x:
        return mydates[int(xx)].strftime('%Y-%m-%d')
    else:
        return ""

ax.xaxis.set_major_locator(ticker.MultipleLocator(10))
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mme))
fig.autofmt_xdate()
plt.show()

As an alternative, I would definitely consider plotting the actual dates.

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

file1=np.load('data/numofdays.npz')

fig,ax=plt.subplots(ncols=1)

y=np.array(file1['arr_0'])

mydates = p.DatetimeIndex(file1['arr_1'])

ax.bar(mydates,y, width=60)

fig.autofmt_xdate()
plt.show()

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