seaborn violin plot tidy

pkm = df_tidy[df_tidy.miso_id == gene_name_to_miso_mxe['PKM'][0]]
fig, ax = plt.subplots(1, figsize=(8,6))
sns.violinplot(pkm.value, pkm.celltype, "points", fig=fig, ax=ax,
           color=[common.p_color, common.n_color, common.m_color,
                                                           common.o_color, 'white'],
                    bw=0.03, order=['iPSC', 'NPSC', 'MotorNeu', 'Outliers', 'pooled'], 
                    alpha=0.75, linewidth=1)
sns.despine()
xmin, xmax, ymin, ymax = ax.axis()
ax.hlines((0.3, 0.7), xmin, xmax, color='k', alpha=0.8, linewidth=0.5)
ax.set_xlim(xmin, xmax)
ax.set_ylim(0, 1);

seaborn violin plot untidy

def celltype_to_long_name(celltype):
    """
    Given a single-letter celltype string, one of 'P', 'M', or 'N',
    (could also be lowercase) return a longer name that can be used for
    figures, e.g. 'iPSC' instead of 'P'
    """
    celltype = celltype.upper()
    if celltype == 'M':
        return common.m_long_name
    elif celltype == 'N':
        return common.n_long_name
    elif celltype == 'P':
        return common.p_long_name
    elif celltype == 'O':
        return common.o_long_name
    elif celltype == 'POOLED':
        return 'pooled'
    elif celltype == 'FAILED':
        return 'failed'
    else:
        raise ValueError('Invalid celltype: %s' % celltype)
        
celltype_to_ids = {'P': common.trusted_p, 'N': common.trusted_n, 
                   'M':common.trusted_m, 
                   'O':common.outliers,
                   'pooled':common.pooled_samples,
                   'failed':failed}
                   
failed = singlecell._Common.read_single_column('/home/obot/projects/singlecell/singlecell/ignore_these_samples.txt')

sample_ids_to_celltype = dict((sample_id, celltype_to_long_name(celltype)) for celltype, 
                               sample_ids in celltype_to_ids.iteritems() for sample_id in sample_ids)




gene_name = 'PKM'
series = mxe_summary.xs('miso_posterior_mean', axis=1, level=1).ix[gene_name_to_miso_mxe[gene_name][0]]
ax = sns.violinplot(series, sample_ids_to_celltype, color=[common.p_color, common.n_color, common.m_color,
                                                           common.o_color, 'white'], inner='points',
                    bw=0.05, order=['iPSC', 'NPSC', 'MotorNeu', 'Outliers', 'pooled'], alpha=0.75)
ax.set_ylim(0, 1)
ax.set_ylabel(gene_name)
sns.despine()