Change tick frequency for datetime axis

Question

I have the following dataframe:

    Date        Prod_01  Prod_02
19  2018-03-01  49870    0.0
20  2018-04-01  47397    0.0
21  2018-05-01  53752    0.0
22  2018-06-01  47111    0.0
23  2018-07-01  53581    0.0
24  2018-08-01  55692    0.0
25  2018-09-01  51886    0.0
26  2018-10-01  56963    0.0
27  2018-11-01  56732    0.0
28  2018-12-01  59196    0.0
29  2019-01-01  57221    5.0
30  2019-02-01  55495    472.0
31  2019-03-01  65394    753.0
32  2019-04-01  59030    1174.0
33  2019-05-01  64466    2793.0
34  2019-06-01  58471    4413.0
35  2019-07-01  64785    6110.0
36  2019-08-01  63774    8360.0
37  2019-09-01  64324    9558.0
38  2019-10-01  65733    11050.0

And I need to plot a time series of the 'Prod_01' column.

The 'Date' column is in the pandas datetime format.

So I used the following command:

plt.figure(figsize=(10,4))
plt.plot('Date', 'Prod_01', data=test, linewidth=2, color='steelblue')
plt.xticks(rotation=45, horizontalalignment='right');

Output:

However, I want to change the frequency of the xticks to one month, so I get one tick and one label for each month.

I have tried the following command:

plt.figure(figsize=(10,4))
plt.plot('Date', 'Prod_01', data=test, linewidth=2, color='steelblue')
plt.xticks(np.arange(1, len(test), 1), test['Date'] ,rotation=45, horizontalalignment='right');

But I get this:

How can I solve this problem? Thanks in advance.

Answer 1

I'm not very familiar with pandas data frames. However, I can't see why this wouldn't work with any pyplot:

According the top SO answer on related post by ImportanceOfBeingErnest:

The spacing between ticklabels is exclusively determined by the space between ticks on the axes.

So, to change the distance between ticks, and the labels you can do this:

Suppose a cluttered and base-10 centered person displays the following graph:

It takes the following code and importing matplotlib.ticker:

import numpy as np
import matplotlib.pyplot as plt
# Import this, too
import matplotlib.ticker as ticker


# Arbitrary graph with x-axis = [-32..32]
x = np.linspace(-32, 32, 1024)
y = np.sinc(x)

# -------------------- Look Here --------------------
# Access plot's axes
axs = plt.axes()
# Set distance between major ticks (which always have labels)
axs.xaxis.set_major_locator(ticker.MultipleLocator(5))
# Sets distance between minor ticks (which don't have labels)
axs.xaxis.set_minor_locator(ticker.MultipleLocator(1))
# -----------------------------------------------------

# Plot and show graph
plt.plot(x, y)
plt.show()

To change where the labels are placed, you can change the distance between the 'major ticks'. You can also change the smaller 'minor ticks' in between, which don't have a number attached. E.g., on a clock, the hour ticks have numbers on them and are larger (major ticks) with smaller, unlabeled ones between marking the minutes (minor ticks).

By changing the --- Look Here --- part to:

# -------------------- Look Here --------------------
# Access plot's axes
axs = plt.axes()
# Set distance between major ticks (which always have labels)
axs.xaxis.set_major_locator(ticker.MultipleLocator(8))
# Sets distance between minor ticks (which don't have labels)
axs.xaxis.set_minor_locator(ticker.MultipleLocator(4))
# -----------------------------------------------------

You can generate the cleaner and more elegant graph below:

Hope that helps!