[FIXED] Matplotlib doesn't display correctly in Visual Studio Code

Issue

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

Solution

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")

Answered By - tdy