version 0.12.0: problems interacting subplots and DataFrame().hist()

[bluefir]

I run Python 2.7.5 on Windows 7 64-bit and IPython 0.13.2.

I have a data frame with some portfolio weights and I do the following:

def weight_histograms(field, name, bins=100):
    if flag_inline:
        plt.figure(figsize=(16, 8))
    else:
        plt.figure()
    plt.subplot(121)
    portfolio_data[field].hist(normed=True, bins=bins)
    plt.title('{}: All'.format(name))
    plt.subplot(122)
    portfolio_data.ix[portfolio_data[field] != 0, field].hist(normed=True, bins=bins)
    plt.title('{}: Non-Zero'.format(name))

With pandas 0.11.0, running

weight_histograms(field_benchmark_weight, 'Benchmark Weights')

in IPython with

%pylab inline

and

flag_inline=True

I get

Doing the same thing with pandas 0.12.0 results in

[cpcloud]

@bluefir while this is being fixed:

fyi you should really be using the plotting API not the pylab stuff that tries to imitate matlab by mutating a lot of global state in the interactive shell (i'm not dissing it, but it makes it difficult to make a somewhat uniform API (in pandas) when you have to keep track of a bunch of global state) for the record i like using the matlab-ish API, but not when i write plotting code for reuse.

here's some code to do what you want that uses the matplotlib API (and doesn't have the above error)

def weight_hists(field, name, bins=100, flag_inline=False):
    if flag_inline:
        figsize = 16, 8
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=figsize)
    portfolio_data[field].hist(ax=ax1, normed=True, bins=bins)
    ax1.set_title('{}: All'.format(name))
    portfolio_data.ix[portfolio_data[field] != 0, field].hist(ax=ax2, normed=True, bins=bins)
    ax2.set_title('{}: Non-Zero'.format(name))

[halleygithub]

I meet this kind problem after upgrading from 0.11 to 0.12 .

In 0.11, df_hist(df[['RT','TExg','TAmt']]) will draw 3 subplot in 1 figure, one subplot for one column data , while in 0.12, only 1 subplot in 1 figure (seems all subplots mix together).

def df_hist(df, title_str="", p=0, bins=None):

    #draw histgram for each dataframe column, filter_dt = dt[(dt>dt.quantile(p)) & (dt<dt.quantile(1-p))]    

    fig = plt.figure()
    plt.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.90)
    plt.subplots_adjust(hspace = 0.3) # the amount of height reserved for white space between subplots, wspace

    col_qty = len(df.columns)

    for i, col in enumerate(df.columns):
        dt = df[col]
        filter_dt = dt[(dt>dt.quantile(p)) & (dt<dt.quantile(1-p))]
        stat = filter_dt.describe().to_dict()
        draw_bins = (math.sqrt(len(dt)) if bins is None else bins) 

        plt.subplot(col_qty, 1, i+1)
        filter_dt.hist(normed=True, color='green', alpha=0.5, bins=draw_bins)
        plt.axis(xmin=stat['min'],xmax=stat['max'])

        mu, sigma, med = stat['mean'], stat['std'], stat['50%']

        plt.title('%s '%(col) + r'$\mu=%0.4f,\ \sigma=%0.4f,\ median=%0.4f, \ p=%0.2f $'%(mu, sigma, med, p), fontproperties=TITLE_FONT)
        plt.axvline(med, linewidth=3, color='r')

    plt.suptitle('Histogram')

    return fig

[cpcloud]

ok i can fix this tonight probably...i've figured out what issue is..

[cpcloud]

nice... this was simple fix...now i need a way to test that there's no overlap.... to the matplotlib source code mobile!

[cpcloud]

@halleygithub use some code here to show code (those are backticks, ASCII code 96) also checkout the github flavored markdown link just up and to the right of where you write a comment in.