Plotting using subplots

[michaelaye]

I am creating the attached plot like this:

fig, axes = subplots(3,3, sharex=True, sharey=True)
for ch in range(1,7):
    axis = axes.flatten()[ch-1]
    cols = some code to map ch to col_names
    df[cols].plot(ax=axis)
# do the same for 3 more channels with different IDs
for ch in range(1,4):
    axis = axes.flatten()[ch-1+6]
    cols = some code to map ch to col_names, slightly different to above
    df[cols].plot(ax=axis)

I have 2 problems with the result:

1. sharex does not seem to work for time axes
2. The last major x-ticklabel of the last row of axes is 10:00, while for the first 2 rows it is 9:00. I confirmed that all columns have data in the last row (index = 2011-04-02 10:00:00.718000) and not NaN which would have been excluded in the plot, potentially.

Possibly the 2 probs are related?

[sinhrks]

Not 100% sure, but this seems to be the same issue as #7801. Based on my understanding:

1. sharex works correctly.
2. ticklabels looks different because major ticklabels are displayed only on bottom axes.

Unfortunately #7801 CANNOT solve this because #7801 will hide minor ticklabels in pandas.tools.plotting._subplots, and will not affect existing axes created by plt.subplots.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

fig, axes = plt.subplots(3, 3, sharex=True)
plt.subplots_adjust(left=0.05, right=0.95, hspace=0.3, wspace=0.3)
df = pd.DataFrame(np.random.randn(10, 9), index=pd.date_range(start='2014-07-01', freq='M', periods=10))
for i, ax in enumerate(axes.ravel()):
    df[i].plot(ax=ax, fontsize=5)

Workaround is use layout kw to create (3, 3) layout using pandas.tools.plotting._subplots (possible after #7736).

[michaelaye]

I don't understand what you are saying, because the idea of sharex is that only the bottom line of graphs shows the x-axis' labels, so why would you state above that sharex is working correctly?

[TomAugspurger]

Closed via #8764