How to plot two pandas time series on same plot with legends and secondary y-axis?

The following solutions work for me. The first places both lines in one legend, the second splits lines into two legends, similar to what you are trying above.

Here is my dataframe

ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list('ABCD'))

One legend solution, credit to this StackOverflow post

plt.figure(figsize=(12,5))
plt.xlabel('Number of requests every 10 minutes')

ax1 = df.A.plot(color='blue', grid=True, label='Count')
ax2 = df.B.plot(color='red', grid=True, secondary_y=True, label='Sum')

h1, l1 = ax1.get_legend_handles_labels()
h2, l2 = ax2.get_legend_handles_labels()


plt.legend(h1+h2, l1+l2, loc=2)
plt.show()

Split legend solution

plt.figure(figsize=(12,5))
plt.xlabel('Number of requests every 10 minutes')

ax1 = df.A.plot(color='blue', grid=True, label='Count')
ax2 = df.B.plot(color='red', grid=True, secondary_y=True, label='Sum')

ax1.legend(loc=1)
ax2.legend(loc=2)

plt.show()

It can be as simple as:

df.loc[:,['A','B']].plot(secondary_y=['B'], mark_right=False, figsize = (20,5), grid=True)

mark_right=False means that 'B' label is on the left axis.