Plot points with numerical label in seaborn and latex title

points_with_label.py

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import rc

sns.set_style("darkgrid")

# for using latex in plt it requires one installation:
# $ sudo apt install dvipng
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
rc('font', **{'family': 'serif', 'serif': ['Palatino']})
rc('text', usetex=True)


def plot_runners(lab, year, names, position_per_cat):
    """
    plot the results of all the students
    using their positions

    :type lab: str
    :type year: str
    :type names: [str]
    :type position_per_cat: np.array
    """
    # calculating scores
    scores = - np.log(position_per_cat)
    tuples = list(zip(scores, names))
    tuples.sort()
    scores = []
    names = []
    for car, cdr in tuples:
        scores.append(car)
        names.append(cdr)

    scores_label = [round(i, 3) for i in scores]
    scores_mean = np.mean(scores)
    scores_std = np.std(scores)

    # ploting
    fig, ax = plt.subplots(figsize=(13, 10), sharex=True)
    ax = sns.pointplot(x=names, y=scores, join=False)

    plt.xlabel('Student', fontsize=18, fontweight='bold')
    plt.ylabel('Score', fontsize=18, fontweight='bold')

    title_car1 = "Running score of the {} ".format(lab)
    title_car2 = "students at 'volta da USP {}'\n".format(year)
    title_car = title_car1 + title_car2
    title_cdr = r"$\displaystyle score = -\log\left(\frac{position}{\#\,category}\right)$"

    fig.suptitle(title_car + title_cdr,
                 fontsize=20,
                 fontweight='bold',
                 y=0.99)

    bbox_props = dict(boxstyle="square,pad=0.3", fc="white", ec="black", lw=0.2)
    box_position_x, box_position_y = ax.get_xticks()[0], scores[-1]

    ax.text(box_position_x,
            box_position_y,
            "$mean = {:.3f},  std = {:.3f}$".format(scores_mean, scores_std),
            size=15,
            bbox=bbox_props)

    for point in zip(ax.get_xticks(), scores_label):
        ax.text(point[0], point[1] + 0.05, point[1], color='g')

    # saving
    filename = "VoltaUSP" + year + lab + ".png"
    plt.savefig(filename)


# inputs
year = '2017'
lab = "IME" 
names_liamf = ['Erika', "Felipe", 'Lucas M.', "Thiago", "Paula", 'Willy']
position_liamf = np.array([45 / 118,
                           21 / 93,
                           38 / 158,
                           137 / 158,
                           53 / 202,
                           8 / 158])

names_music = ["Oberlan", " Shayenne"]
position_music = np.array([5 / 74, 174 / 202]) 

names_system = ["Lucas D.", "Dylan",  "Rodrigo"]
position_system = np.array([33 / 131, 80 / 158, 10 / 131])

all_names = np.concatenate([names_liamf, names_music, names_system], 0)
all_positions = np.concatenate([position_liamf, position_music, position_system], 0)

plot_runners(lab, year, all_names, all_positions)