Matplotlib doesn't display correctly in Visual Studio Code

user_15408229 0
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I am trying to create a plot made of 5 subplots made of simple line graphs using Matplotlib and Pandas on Visual Studio code. However, for some reason the image always looks very small and clumped up even if I make the figure very big. I tried modifying the space between figures with subplots_adjust but that doesn't change anything.

Here is my code

ax1 = plt.subplot(1, 5, 1)
ax1 = plt.plot(returns["MSFT"])
plt.xlabel("Date")
plt.ylabel("Daily MSFT Returns")
plt.title("MSFT Returns Over Time")

ax2 = plt.subplot(1, 5, 2)
ax2 = plt.plot(returns["AMZN"])
plt.xlabel("Date")
plt.ylabel("Daily AMZN Returns")
plt.title("AMZN Returns Over Time")

ax3 = plt.subplot(1, 5, 3)
ax3 = plt.plot(returns["AAPL"])
plt.xlabel("Date")
plt.ylabel("Daily AAPL Returns")
plt.title("AAPL Returns Over Time")

ax4 = plt.subplot(1, 5, 4)
ax4 = plt.plot(returns["GOOG"])
plt.xlabel("Date")
plt.ylabel("Daily GOOG Returns")
plt.title("GOOG Returns Over Time")

ax5 = plt.subplot(1, 5, 5)
ax5 = plt.plot(returns["FB"])
plt.xlabel("Date")
plt.ylabel("Daily FB Returns")
plt.title("FB Returns Over Time")

plt.figure(figsize=(100, 100))
plt.subplots_adjust(wspace = 10)
plt.show()

figure displayed

visual-studio-code matplotlib visual-studio
2 Answers

Update: As BigBen mentioned, you can further simplify with a loop. For example, here we put all subplot axes in axes and company names in names, then zip and iterate:

fix, axes = plt.subplots(nrows=1, ncols=5, figsize=(20, 5))
names = ['MSFT', 'AMZN', 'AAPL', 'GOOG', 'FB']

for ax, name in zip(axes, names):
    ax.plot(returns[name])
    ax.set_ylabel(f'Daily {name} Returns')
    ax.set_title(f'{name} Returns Over Time')

Generally it's easier to first create the subplot axes ax1, ..., ax5 using plt.subplots() with figsize. Then operate on those premade axes handles like ax1.plot() instead of plt.plot(), ax1.set_xlabel() instead of plt.xlabel(), etc.

# first create ax1~ax5
fig, (ax1,ax2,ax3,ax4,ax5) = plt.subplots(nrows=1, ncols=5, figsize=(20, 5))

ax1.plot(returns["MSFT"])               # not plt.plot(...)
ax1.set_xlabel("Date")                  # not plt.xlabel(...)
ax1.set_ylabel("Daily MSFT Returns")    # not plt.ylabel(...)
ax1.set_title("MSFT Returns Over Time") # not plt.title(...)

ax2.plot(returns["AMZN"])
ax2.set_xlabel("Date")
ax2.set_ylabel("Daily AMZN Returns")
ax2.set_title("AMZN Returns Over Time")

ax3.plot(returns["AAPL"])
ax3.set_xlabel("Date")
ax3.set_ylabel("Daily AAPL Returns")
ax3.set_title("AAPL Returns Over Time")

ax4.plot(returns["GOOG"])
ax4.set_xlabel("Date")
ax4.set_ylabel("Daily GOOG Returns")
ax4.set_title("GOOG Returns Over Time")

ax5.plot(returns["FB"])
ax5.set_xlabel("Date")
ax5.set_ylabel("Daily FB Returns")
ax5.set_title("FB Returns Over Time")

plt.subplots() example

user_131383640

A couple of suggestions that might help- first matplotlib has a function "tight_layout" which can help set the white space sensibly and reduce the number of tick labels. documentation. To use it simply call plt.tight_layout() just before plt.show()

But this won't solve the problem of there being lots of text on your figure. You could try and save text by using a suptitle of "Stock returns over time" as shown here and simply referring to each plot by the stock name for the sub plot titles.

It might also be worth considering if a different style of plot could do a better job. If the returns are of similar magnitude and over the same time period it may make more sense to have them as different coloured lines on the same axes, with a legend showing identifying the stocks

user_155075790
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