Htykuut

I have this simple python code that generates a simple X date y decimal plot.

My goal was to set the ticks to be the one unit less than the minimum TO the one unit plus the maximum, see code and plot below.

I don't see why it would not shows the X tick properly, the Y tick shows just fine.

import matplotlib.pyplot as plt

import pandas as pd



fig = plt.figure(facecolor="#979899")

ax = plt.gca()

ax.set_facecolor("#d1d1d1")

ax.set_xlim(pd.to_datetime(["2018-11-18"]),pd.to_datetime(["2018-11-22"]))



plt.grid(True)

plt.title("This is a title",fontsize=16)



plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0])

plt.xticks(pd.to_datetime(["2018-11-18","2018-11-20","2018-11-22"]))



x1 = pd.to_datetime(["2018-11-19","2018-11-20","2018-11-21"])

y1 = [0.18,0.32,0.21]





for i,item in enumerate(y1):

    xP = x1[i]

    yP = y1[i]

    plt.text(xP,yP,str(item)+"%",fontsize=11)



plt.scatter(x1,y1)

plt.plot(x1,y1)

plt.show()

You provide integers for the dates. So Matplotlib treats it like any number. And it tries to be smart about large numbers that are close together:

The default formatter identifies when the x-data being plotted is a
small range on top of a large off set. To reduce the chances that the
ticklabels overlap the ticks are labeled as deltas from a fixed
offset. For example:

ax.plot(np.arange(2000, 2010), range(10)) will have tick of 0-9 with
an offset of +2e3. If this is not desired turn off the use of the
offset on the default formatter:

ax.get_xaxis().get_major_formatter().set_useOffset(False) set the
rcParam axes.formatter.useoffset=False to turn it off globally, or set
a different formatter.
This is from the docs of the matplotlib.ticker module.

I solved the issue by converting to datetime object. Find solution below:

import matplotlib.pyplot as plt

import datetime



fig = plt.figure(facecolor="#979899")

ax = plt.gca()

ax.set_facecolor("#d1d1d1")

plt.grid(True)

plt.title("This is a title",fontsize=16)



plt.xticks([datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)],["11/20","11/21","11/22"])

plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],["0.0","0.1","0.2","0.3","0.4","0.5","0.6","0.7","0.8","0.9","1.0"])



x1 = [datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)]

y1 = [0.18,0.32,0.21]



for i,item in enumerate(y1):

    xP = x1[i]

    yP = y1[i]

    plt.text(xP,yP,str(item)+"%",fontsize=11)



plt.plot(x1,y1)

plt.show()