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Suppose I have a DataFrame of created like this:
import pandas as pd
s1 = pd.Series(['a', 'b', 'a', 'c', 'a', 'b'])
s2 = pd.Series(['a', 'f', 'a', 'd', 'a', 'f', 'f'])
d = pd.DataFrame({'s1': s1, 's2', s2})
There is quite a lot of sparsity in the strings in the real data. I would like to create histograms of the occurrence of strings that looks like what is generated by d.hist() (eg. with subplots) for s1 and s2 (one per subplot).
Just doing d.hist() gives this error:
/Library/Python/2.7/site-packages/pandas/tools/plotting.pyc in hist_frame(data, column, by, grid, xlabelsize, xrot, ylabelsize, yrot, ax, sharex, sharey, **kwds)
1725 ax.xaxis.set_visible(True)
1726 ax.yaxis.set_visible(True)
-> 1727 ax.hist(data[col].dropna().values, **kwds)
1728 ax.set_title(col)
1729 ax.grid(grid)
/Library/Python/2.7/site-packages/matplotlib/axes.pyc in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
8099 # this will automatically overwrite bins,
8100 # so that each histogram uses the same bins
-> 8101 m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
8102 if mlast is None:
8103 mlast = np.zeros(len(bins)-1, m.dtype)
/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/function_base.pyc in histogram(a, bins, range, normed, weights, density)
167 else:
168 range = (a.min(), a.max())
--> 169 mn, mx = [mi+0.0 for mi in range]
170 if mn == mx:
171 mn -= 0.5
TypeError: cannot concatenate 'str' and 'float' objects
I suppose I could manually go through each series, do a value_counts(), then plot it as a bar plot, and manually create the subplots. I wanted t