I would like to produce a subplot from data 4-column DataFrame into 2-rows and 2-columns.
df = pd.DataFrame(np.random.randn(6,4),index=pd.date_range('1/1/2000',periods=6, freq='1h'))
However, below will give a 4-row and 1-column plot
df.plot(use_index=False, title=f, subplots=True, sharey=True, figsize=(8, 6))
In current versions of Pandas, DataFrame.plot features the layout keyword for this purpose.
df.plot(subplots=True, layout=(2,2), ...)
cplcloud's answer works, but following code will give you a bit more structure so that you can start configuring more if you do not need the loop.
fig, axes = plt.subplots(nrows=2, ncols=2)
fig.set_figheight(6)
fig.set_figwidth(8)
df[0].plot(ax=axes[0,0], style='r', label='Series'); axes[0,0].set_title(0)
df[1].plot(ax=axes[0,1]); axes[0,1].set_title(1)
df[2].plot(ax=axes[1,0]); axes[1,0].set_title(2)
df[3].plot(ax=axes[1,1]); axes[1,1].set_title(3)
fig.tight_layout()
Added some example on axis 0 to show how you can further configure it.
import matplotlib.pyplot as plt, then something likefor i in df: plt.subplot(2,2,i+1);plt.plot(df[i]);figshapeargument...