Matplotlib x-axis and secondary y-axis customization questions

Question

Data - we import historical yields of the ten and thirty year Treasury and calculate the spread (difference) between the two (this block of code is good; feel free so skip):

#Import statements 
import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker

#Constants 
start_date = "2018-01-01"
end_date = "2023-01-01"

#Pull in data
tenYear_master = yf.download('^TNX', start_date, end_date)
thirtyYear_master = yf.download('^TYX', start_date, end_date)

#Trim DataFrames to only include 'Adj Close columns'
tenYear = tenYear_master['Adj Close'].to_frame()
thirtyYear = thirtyYear_master['Adj Close'].to_frame()

#Rename columns
tenYear.rename(columns = {'Adj Close' : 'Adj Close - Ten Year'}, inplace= True)
thirtyYear.rename(columns = {'Adj Close' : 'Adj Close - Thirty Year'}, inplace= True)

#Join DataFrames
data = tenYear.join(thirtyYear)

#Add column for difference (spread)
data['Spread'] = data['Adj Close - Thirty Year'] - data['Adj Close - Ten Year']

data

This block is also good.

'''Plot data'''
#Delete top, left, and right borders from figure 
plt.rcParams['axes.spines.top'] = False
plt.rcParams['axes.spines.left'] = False
plt.rcParams['axes.spines.right'] = False
fig, ax = plt.subplots(figsize = (15,10))
data.plot(ax = ax, secondary_y = ['Spread'], ylabel = 'Yield', legend = False);

'''Change left y-axis tick labels to percentage'''
left_yticks = ax.get_yticks().tolist()
ax.yaxis.set_major_locator(mticker.FixedLocator(left_yticks))
ax.set_yticklabels((("%.1f" % tick) + '%') for tick in left_yticks);

#Add legend 
fig.legend(loc="upper center", ncol = 3, frameon = False)
fig.tight_layout()
plt.show()

I have questions concerning two features of the graph that I want to customize:

1. The x-axis currently has a tick and tick label for every year. How can I change this so that there is a tick and tick label for every 3 months in the form MMM-YY? (see picture below)

2. The spread was calculated as thirty year yield - ten year yield. Say I want to change the RIGHT y-axis tick labels so that their sign is flipped, but I want to leave both the original data and curves alone (for the sake of argument; bear with me, there is logic underlying this). In other words, the right y-axis tick labels currently go from -0.2 at the bottom to 0.8 at the top. How can I change them so that they go from 0.2 at the bottom to -0.8 at the top without changing anything about the data or curves? This is purely a cosmetic change of the right y-axis tick labels.

I tried doing the following:

'''Change right y-axis tick labels'''
right_yticks = (ax.right_ax).get_yticks().tolist()
#Loop through and multiply each right y-axis tick label by -1
for index, value in enumerate(right_yticks):
  right_yticks[index] = value*(-1)
(ax.right_ax).yaxis.set_major_locator(mticker.FixedLocator(right_yticks))
(ax.right_ax).set_yticklabels(right_yticks)

But I got this:

Note how the right y-axis is incomplete.

I'd appreciate any help. Thank you!

Answer 1

Let's create some data:

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np

days = np.array(["2022-01-01", "2022-07-01", "2023-02-15", "2023-11-15", "2024-03-03"],
                 dtype = "datetime64")
val = np.array([20, 20, -10, -10, 10])

For the date in the x-axis, we import matplotlib.dates, which provides the month locator and the date formater. The locator sets the ticks each 3 months, and the formater sets the way the labels are displayed (month-00).

For the y-axis data, you require changing the sign of the data (hence the negative sign in ax2.plot(), but you want the curve in the same position, so afterwards you need to invert the axis. And so, the curves in both plots are identical, but the y-axis values have different signs and directions.

fig, (ax1, ax2) = plt.subplots(figsize = (10,5), nrows = 2)

ax1.plot(days, val, marker = "x")
# set the locator to Jan, Apr, Jul, Oct
ax1.xaxis.set_major_locator(mdates.MonthLocator( bymonth = (1, 4, 7, 10) ))
# set the formater for month-year, with lower y to show only two digits
ax1.xaxis.set_major_formatter(mdates.DateFormatter("%b-%y"))

# change the sign of the y data plotted
ax2.plot(days, -val, marker = "x")
#invert the y axis
ax2.invert_yaxis()
# set the locator to Jan, Apr, Jul, Oct
ax2.xaxis.set_major_locator(mdates.MonthLocator( bymonth = (1, 4, 7, 10) ))
# set the formater for month-year, with lower y to show only two digits
ax2.xaxis.set_major_formatter(mdates.DateFormatter("%b-%y"))

plt.show()