How to do multi-row layout using matplotlib subplots-CodePudding

This is a question about how to properly organize subplots, not how to create stacked bars.

I have the following dataframe:

     corpus group  mono p  non p  plus p  minus p
0  fairview   all      49     51      49        0
1      i2b2   all      46     54      46        0
2    mipacq   all      44     56      43        1

and want to arrange the output as given in the two attached figures so that I get ncolumns and 2-rows, instead of two separate subplots with 1 row each (so in this case, there would be 2-rows, 3-columns on a single subplot instead of 1-row, 3-columns on 2 subplots):

I am generating these two figures as separate subplots using the following code:

data = <above dataframe>
semgroups = ['all']
corpus = ['fairview', 'i2b2', 'mipacq']
for sg in semgroups:

    i = semgroups.index(sg)
    ix = i   7

    ncols = len(set(data.corpus.tolist()))
    nrows = len(set(data.group.tolist()))

    fig = plt.figure()
    
    fig, axs = plt.subplots(1, ncols, sharey=True)

    for ax,(idx,row) in zip(axs.flat, data.iterrows()):
        # I WANT TO PLOT BOTH ROWS on same subplot
        #row[['mono p', 'non p']].plot.bar(ax=ax, color=['C0','C1'])
        row[['plus p', 'minus p']].plot.bar(ax=ax, color=['C0','C1'])
        if row['corpus'] == 'fairview':
            corpus = 'Fairview'
            label =  '(d) '
        elif row['corpus'] == 'mipacq':
            corpus = 'MiPACQ'
            if ncols == 3:
                label = '(f) '
            else:
                label = '(b) '
        else:
            corpus = 'i2b2'
            label = '(e) '
        
        ax.set_title(label   corpus)
        ax.tick_params(axis='x', labelrotation = 45)
    
    if sg == 'all':
        sg = 'All groups'

    # Defining custom 'xlim' and 'ylim' values.
    custom_ylim = (0, 60)

    # Setting the values for all axes.
    plt.setp(axs, ylim=custom_ylim)
    fig.suptitle('Figure '   str(ix)   ' '   sg)

In the code above, I iterate through my df grabbing the following rows to generate both separate subplots:

# BUT, I WANT TO PLOT BOTH ROWS ON SAME SUBPLOT
row[['mono p', 'non p']].plot.bar(ax=ax, color=['C0','C1'])
row[['plus p', 'minus p']].plot.bar(ax=ax, color=['C0','C1'])

No matter how I do this I cannot get the desired two rows in a single subplot(I always get an empty row of plots with no data on the second row).

CodePudding user response：

See inline comments
Tested in python 3.8.12, pandas 1.3.3, matplotlib 3.4.3, seaborn 0.11.2

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns  # seaborn is a high-level api for matplotlib

# sample dataframe
data = {'corpus': ['fairview', 'i2b2', 'mipacq'], 'group': ['all', 'all', 'all'], 'mono p': [49, 46, 44], 'non p': [51, 54, 56], 'plus p': [49, 46, 43], 'minus p': [0, 0, 1]}
df = pd.DataFrame(data)

semgroups = df.group.unique()  # unique groups
corpus = df.corpus.unique()  # unique corpus
rows = [['mono p', 'non p'], ['plus p', 'minus p']]  # columns for each row of plots
for sg in semgroups:
    
    i = semgroups.index(sg)
    ix = i   7

    ncols = len(corpus)  # 3 columns for the example
    nrows = len(rows)  # 2 rows for the example

    # create a figure with 2 rows of 3 columns: axes is a 2x3 array of <AxesSubplot:>
    fig, axes = plt.subplots(nrows, ncols, sharey=True, figsize=(12, 10))

    # iterate through each plot row combined with a list from rows
    for axe, row in zip(axes, rows):
        # iterate through each plot column of the current row
        for i, ax in enumerate(axe):
            
            # select the data for each plot
            data = df.loc[df.group.eq(sg) & df.corpus.eq(corpus[i]), row]
            
            # plot the dataframe, but setting the bar color is more difficult
#             data.T.plot(kind='bar', legend=False, ax=ax)
            
            # plot the data with seaborn, which is easier to color the bars
            sns.barplot(data=data, ax=ax)

            if corpus[i] == 'fairview':
                l2 = 'Fairview'
                l1 =  '(d) '
            elif corpus[i] == 'mipacq':
                l2 = 'MiPACQ'
                if ncols == 3:
                    l1 = '(f) '
                else:
                    l1 = '(b) '
            else:
                l2 = 'i2b2'
                l1 = '(e) '

            ax.set_title(l1   l2)
            ax.tick_params(axis='x', labelrotation = 45)
    
    if sg == 'all':
        sg = 'All groups'

    # Defining custom 'xlim' and 'ylim' values.
    custom_ylim = (0, 60)

    # Setting the values for all axes.
    plt.setp(axes, ylim=custom_ylim)
    fig.suptitle('Figure '   str(ix)   ' '   sg)
    fig.tight_layout()
    plt.show()