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

Question

I want to plot two time series on the same plot with same x-axis and secondary y-axis. I have somehow achieved this, but two legends are overlapping and is unable to give label to x-axis and secondary y-axis.I tried putting two legend at upper-left and upper-right, but it is still not working.

Code:

plt.figure(figsize=(12,5))

# Number of request every 10 minutes
log_10minutely_count_Series = log_df['IP'].resample('10min').count()
log_10minutely_count_Series.name="Count"
log_10minutely_count_Series.plot(color='blue', grid=True)
plt.legend(loc='upper left')
plt.xlabel('Number of request ever 10 minute')

# Sum of response size over each 10 minute
log_10minutely_sum_Series = log_df['Bytes'].resample('10min').sum()
log_10minutely_sum_Series.name = 'Sum'
log_10minutely_sum_Series.plot(color='red',grid=True, secondary_y=True)
plt.legend(loc='upper right')
plt.show()

Thanks in advance

Answer 1

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()