Проблема с Matplotlib между MacOS и Raspberry Pi

У меня есть Raspberry Pi, работающий на некотором оборудовании и постоянно генерирующий данные. Каждый день я собираю данные в фрейме данных pandas, и он отправляет сводное электронное письмо. Это электронное письмо должно содержать красивую диаграмму, показывающую данные с течением времени. Тестирование на моей основной машине (последняя версия MacOS) работает прекрасно. Однако пи выводит пустые графики. Оси, метки, цвета и все, кроме самих графиков. Просто пустой график. На обеих машинах работает matplotlib 3.5.1. Пожалуйста, помогите мне понять, почему графики не отображаются на одной машине, но прекрасно работают на другой.

#!/usr/bin/env python

import dill
import pandas
import datetime
from datetime import timedelta
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import subprocess

class Report():
  def __init__(self, datafile):
    # Saved dataframes
    self.file = datafile

  def runReport(self):
    # Open data
    saveIn = open(self.file, 'rb')
    data = dill.load(saveIn)
    # Close file
    saveIn.close()
    # Alias dataframe
    systemData = data['systemReadings']

    # Declare chart, set output size
    fig = plt.figure(figsize = (14, 8.75))

    ## Plot1
    # Create plot1 plot sharing an X-axis with Plot5
    plot1 = fig.add_subplot()
    # Display y-axis labels alongside Plot5
    plot1.yaxis.tick_left()
    # Display tick labels to left of tick line
    rspine = plot1.spines['left']
    # Display y-axis label to the left of the chart
    plot1.yaxis.set_label_position("left")
    # Y-axis range
    plt.ylim((7.0, 8.5))
    # Divide y-axis into 10 ticks
    plt.locator_params(axis = 'y', nbins = 10)
    # Limit x-axis to 00:00 - 23:59 range
    plot1.set_xlim([datetime.date(2022,3,6), datetime.date(2022,3,7)])
    # Link data and color line
    plot1.plot(systemData['Plot1'], color = 'k', label = 'Plot1')
    # Shares scale and label with Plot5

    ## Plot2
    # Create Plot2 plot on X-axis with plot1
    plot2 = plot1.twinx()
    # Display y-axis labels to the right of scale line
    rspine = plot2.spines['right']
    # Adjust location of axis/labels so they're not on top of the other dataset sharing that side of the chart
    rspine.set_position(('axes', 1.05))
    # Y-axis range
    plt.ylim((-0.05, 1))
    # Divide y-axis into 10 tickmarks
    plt.locator_params(axis = 'y', nbins = 10)
    # Link data and line color
    plot2.plot(systemData['Plot2'], color = 'orange', label = 'Plot2')
    # Label and label color
    plot2.set_ylabel('Plot2', color = 'orange')

    ## Plo3
    # Create Estimated Plot3 plot on same X-axis with plot1
    plot3 = plot1.twinx()
    # Display ticks on left side of chart
    plot3.yaxis.tick_left()
    # Display tick labels to left of tick line
    rspine = plot3.spines['left']
    # Display y-axis label to the left of the chart
    plot3.yaxis.set_label_position("left")
    # Adjust location of axis/labels so they're not on top of the other dataset sharing that side of the chart
    rspine.set_position(('axes', -0.05))
    # Y-axis range
    plt.ylim((-2, 2))
    # Divide y-axis into 20 tick marks
    plt.locator_params(axis = 'y', nbins = 20)
    # Link data and color line
    plot3.plot(systemData['Plot3'], color = 'limegreen', label = 'Plot3')
    # Label and label color
    plot3.set_ylabel('Plot3', color = 'limegreen')

    ## Plot4
    # Create Plot4 sharing an X-axis with plot1 plot
    plot4 = plot1.twinx()
    # Display y-axis labels to the right of scale line
    rspine = plot4.spines['right']
    # Y-axis range
    plt.ylim((-0.05, 0.5))
    # Divide y-axis in to 10 ticks
    plt.locator_params(axis = 'y', nbins = 10)
    # Link data and color line
    plot4.plot(systemData['Plot4'], color = 'r', label = 'Plot4')
    # Label and label color
    plot4.set_ylabel('Plot4', color = 'b')

    ## plot5
    # Create Plot5 sharing an X-axis with plot1 plot
    plot5 = plot1.twinx()
    # Display ticks on left side of chart
    plot5.yaxis.tick_left()
    # Display tick labels to left of tick line
    rspine = plot3.spines['left']
    # Display y-axis label to the left of the chart
    plot5.yaxis.set_label_position("left")
    # Adjust location of axis/labels so they're not on top of the other dataset sharing that side of the chart
    rspine.set_position(('axes', -0.05))
    # Y-axis range
    plt.ylim((7.0, 8.5))
    # Display y-axis grid lines
    plot5.yaxis.grid()
    # Divide y-axis into 10 ticks
    plt.locator_params(axis = 'y', nbins = 10)
    # Link data and color line
    # Raw
    plot5.plot(systemData['Plot5'], color = 'r', label = 'Plot5')
    # Label and label color
    plot5.set_ylabel('Plot5', color = 'r')

    ## Overall chart formatting
    # Format x-axis hour labels
    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%I:%M %p'))
    # Only tick on each hour
    plt.gca().xaxis.set_major_locator(mdates.HourLocator(interval = 1))
    # Display labels at an angle for space
    fig.autofmt_xdate()
    # Place legend below chart
    fig.legend(loc = 'lower center', ncol = 5)

    # Display final chart
    plt.show()


report = Report()
report.runReport()