Why Are My Matplotlib Y-Axis Values Unordered and How to Fix It?

Matplotlib y Axis Values Are Not Ordered: A Solution

In matplotlib, the y-axis values may appear unordered when plotting data from a CSV file. To address this, it is crucial to ensure that the data is handled as numerical values instead of strings.

Consider the following code:

<code class="python">I020 = [ line.strip('\n').split(",") for line in open(r'D:\Users\a0476\Anaconda3\TickData\PV5sdata1.csv')][1:]
Time = [ datetime.datetime.strptime(line[0],"%H%M%S%f") for line in I020 ]
Time1 = [ mdates.date2num(line) for line in Time ]
Solar = [ line[1] for line in I020 ]

# Convert y-axis data to floats
Solar = [float(line[1]) for line in I020]

xs = np.array(Time1)
ys = np.array(Solar)

fig, ax = plt.subplots() # using matplotlib's Object Oriented API

ax.set_title('Solar data')
ax.set_xlabel('Time')
ax.set_ylabel('Solar')
ax.plot_date(xs, ys, 'k-')

hfmt = mdates.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(hfmt)
plt.gcf().autofmt_xdate()

plt.show()</code>

By casting the y-axis data (Solar) to floats, the code correctly interprets the values as numerical, leading to an ordered y-axis.

Additionally, enabling auto-formatting of the x-axis (plt.gcf().autofmt_xdate()) improves the layout and readability of the plot. This is especially beneficial when dealing with date/time data.

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