Box Plotting top ten values of a column in pandas

I have the a large dataframe where I calculate the p value using a t-test for each row. I now want to have a boxplot of the row with the top ten of lowest p-values.

LeadSNPs = pd.unique(candidate_genes.LeadSNP) #rs3184504 rs531612
gene_counts_per_snp_df = pd.DataFrame.empty
save_path = "../figures/SM5_gene_counts/"
for LeadSNP_cnt, LeadSNP in enumerate(LeadSNPs):
    print(LeadSNP)
    candidate_genes_per_SNP = candidate_genes.Target[np.where(candidate_genes.LeadSNP==LeadSNP)[0]]
    region = pd.unique(candidate_genes.Region[np.where(candidate_genes.LeadSNP==LeadSNP)[0]])
    first_gene_flag = 1
    for gene_cnt, target_gene in enumerate(candidate_genes_per_SNP):
        gene_indexes = candidate_genes_per_SNP.index
        PRE = candidate_genes['sumOfWeightedWeights (PRE)'][gene_indexes[gene_cnt]]
        print(target_gene)
        ensembl_id = get_ensembl_id(target_gene)
        print(ensembl_id)
        if pd.isnull(ensembl_id):
            pass
        else:
            gene_counts_df = get_gene_counts_df(ensembl_id)
            if gene_counts_df.shape[0]==0:
                print('no ensemble id found in gene counts!')
            else:
                gene_counts_df = gene_counts_df.melt(id_vars=["Gene"], var_name='compartment', value_name='count')
                gene_counts_df = reshape_gene_counts_df(gene_counts_df)
                gene_counts_df['target_gene'] = target_gene
                gene_counts_df['PRE'] = PRE
                gene_counts_df['pval_ftest']= np.nan
                pop3= gene_counts_df.loc[(gene_counts_df['target_gene']==target_gene) & (gene_counts_df['compartment']=='CSF_N')]['count']
                pop4 = gene_counts_df.loc[(gene_counts_df['target_gene']==target_gene) & (gene_counts_df['compartment']=='PB_N')]['count']
                pval1 = stats.ttest_ind(pop3, pop4)[1]
                gene_counts_df.loc[(gene_counts_df['target_gene']==target_gene) & (gene_counts_df['compartment'].isin(['CSF_N','PB_N'])),"pval_ftest"]= pval_ftest
                if first_gene_flag == 1:
                    gene_counts_per_snp_df = gene_counts_df
first_gene_flag = 0
                else:
                    gene_counts_per_snp_df = pd.concat([gene_counts_per_snp_df, gene_counts_df])
    gene_counts_per_snp_df['LeadSNP'] = LeadSNP
    if LeadSNP_cnt == 0:
        all_gene_counts = gene_counts_per_snp_df
    else:
        all_gene_counts = pd.concat([all_gene_counts, gene_counts_per_snp_df])
all_gene_counts = pd.DataFrame.reset_index(all_gene_counts)
plot_top_genes_snps(all_gene_counts_per_comp, 'target_gene')

and the plotting code is given here

def plot_top_genes_snps(all_gene_counts_per_comp, x_label):
    
    sns.set(style="white")
    sns.set_context("poster")
    palette = sns.color_palette("colorblind", 10)
    
    fig, ax = plt.subplots(figsize=(25,4))
    g = sns.boxplot(ax=ax, y='count', x=x_label, data=all_gene_counts_per_comp, hue = 'compartment', showfliers=False, palette=palette, hue_order=comp_order)
    ax.set_xticklabels(ax.get_xticklabels(), rotation=45, horizontalalignment='right')
    handles, _ = ax.get_legend_handles_labels()
    current_legends = []
    for str_ind in range(len(handles)):
        current_legends.append(comp_dict[handles[str_ind].get_label()])
    ax.legend(handles, current_legends, bbox_to_anchor=(1, 1), loc=2)
    ax.yaxis.grid()
    sns.set(font_scale = 2)
    plt.xlabel('')
    plt.ylabel('Gene count')
    # plt.savefig(save_path+str(LeadSNP)+'.pdf', bbox_inches='tight')
    plt.show()

For context, I want the top ten 'target_gene' with the lowest p values. However this is the plot I am getting

allgenesandpvalues

How do I extract only the ten lowest pvalues and box plot them.