子图辅助轴-Python，matplotlib

Question

I have a dataframe called conversionRate like this:

| State| Apps  | Loans| conversionratio|
2013-01-01  IL      1165    152   13.047210
2013-01-01  NJ      2210    756   34.208145
2013-01-01  TX      1454    73    5.020633
2013-02-01  CA      2265    400   17.660044
2013-02-01  IL      1073    168   15.657036
2013-02-01  NJ      2036    739   36.296660
2013-02-01  TX      1370    63    4.598540
2013-03-01  CA      2545    548   21.532417
2013-03-01  IL      1108    172   15.523466

I intend to plot the number of apps and number of loans in the primary Y axis and the Conversion Ratio in the secondary axis for each state.

I tried the below code:

import math
rows =int(math.ceil(len(pd.Series.unique(conversionRate['State']))/2))
    fig, axes = plt.subplots(nrows=rows, ncols=2, figsize=(10, 10),sharex=True, sharey=False)
    columnCounter = itertools.cycle([0,1])
    rowCounter1    = 0
    for element in pd.Series.unique(conversionRate['State']):
        rowCounter  = (rowCounter1)//2
        rowCounter1 = (rowCounter1+1)
        subSample = conversionRate[conversionRate['State']==element]
        axis=axes[rowCounter,next(columnCounter)]
        #ax2 = axis.twinx()
        subSample.plot(y=['Loans', 'Apps'],secondary_y=['conversionratio'],\
                              ax=axis)

I end up with a figure like the below:

The question is how do I get the secondary axis line to show? If I try the below (per the manual setting secondary_y in plot() should selectively plot those columns in the secondary axis), I see only the line I plot on the secondary axis. There must be something simple and obvious I am missing. I can't figure out what it is! Can any guru please help?

subSample.plot(secondary_y=['conversionratio'],ax=axis)

Answer 1

You need to include conversionration in y=['Loans', 'Apps','conversionratio'] as well as in secondary_y ... or better yet leave that parameter out, since you're plotting all the columns.

rows =int(math.ceil(len(pd.Series.unique(conversionRate['State']))/2))
fig, axes = plt.subplots(nrows=rows, ncols=2, figsize=(10, 
10),sharex=True, sharey=False)
columnCounter = itertools.cycle([0,1])
rowCounter1    = 0
for element in pd.Series.unique(conversionRate['State']):
    rowCounter  = (rowCounter1)//2
    rowCounter1 = (rowCounter1+1)
    subSample = conversionRate[conversionRate['State']==element]
    axis=axes[rowCounter,next(columnCounter)]
    #ax2 = axis.twinx()
    subSample.plot(secondary_y=['conversionratio'], ax=axis)