Visualization of our kicker game scores (matplotlib)

analyze_kicker_scores_matplotlib.py

import re
import json
import matplotlib.pyplot as plt


j_file = open('/home/dmgl/Downloads/Telegram Desktop/ChatExport_2020-09-04/result.json', 'r')
j = json.load(j_file)

s_type = {'type': 'hashtag', 'text': '#scores'}

scores = [] # list of lists with score pairs [[5, 4], [5, 5], [5, 6], [7, 7], [8, 8], [9, 8], [9, 9], [10, 9], ...]
dates = [] # list of strings dates ['2017-09-04T20:25:41', '2017-09-05T18:18:35', '2017-09-05T20:42:58', ...]

for message in j['messages']:
    for text in message['text']:
        if text == s_type:
            date = message['date']
            # print(message)
            try:
                score = re.findall(r"[-+]?\d*\.\d+|\d+", message['text'][1])
                # print(message['text'])
                # print(date, score)
            except:
                pass

            scores.append(score)
            dates.append(date)

team1 = "GALOCHKIN, KLIMOV"
team2 = "OVCHAROV, STANOTIN"

times = [ d for d in range(len(dates)) ]
scores = [ [int(x[0]), int(x[1])] for x in scores ]


def variant1():

    # VARIANT 1 - SHOW SUMMARY PROGRESS IN SCORES

    x1 = times
    x2 = times
    y1 = [ x[0] for x in scores ]
    y2 = [ x[1] for x in scores ]

    with plt.xkcd():

        fig, axs = plt.subplots(figsize=(30, 10))

        axs.plot(x1, y1, label=team1)
        axs.plot(x2, y2, label=team2)

        axs.set(xlabel='GAMES', ylabel='SCORES')

        fig.suptitle('KICKER')
        # fig.tight_layout()

        fig.savefig("KICKER_SCORES_GRAPH_SUMMARY.PNG", bbox_inches='tight')

        plt.legend()
        plt.show()


def variant2():

    # VARIANT 2 - SHOW DIFF BETWEEN TEAMS SCORES

    x1 = times
    x2 = times
    y1 = []
    y2 = []
    for s in scores:
        y1.append( (s[0]-s[1])/2 )
        y2.append( (s[1]-s[0])/2 )

    def get_triumph_times(scores):

        max1,max2 = (0, 0)

        for pair in scores:
            if pair[0] > pair[1]:
                new_max1 = pair[0] - pair[1]
                new_ts1 = scores.index(pair)
                if new_max1 > max1:
                    max1 = new_max1
                    ts1 = new_ts1
            else:
                new_max2 = pair[1] - pair[0]
                new_ts2 = scores.index(pair)
                if new_max2 > max2:
                    max2 = new_max2
                    ts2 = new_ts2

        dt1 = dates[ts1]
        dt2 = dates[ts2]

        return { team1: (ts1, dt1, max1),
                team2: (ts2, dt2, max2) }


    triumph_times = get_triumph_times(scores)


    with plt.xkcd():

        fig, axs = plt.subplots(figsize=(30, 10))
        axs.plot(x1, y1, label=team1)
        axs.plot(x2, y2, label=team2)

        axs.set(xlabel='GAMES', ylabel='SCORES')

        fig.suptitle('KICKER')
        # fig.tight_layout()

        half = times[ -int(len(times)/2) ]

        plt.annotate(
            'THE BEGINNING ' + dates[0],
            xy=(times[0], 0),
            xytext=(half, -1.5),
            arrowprops=dict(arrowstyle='->'),
            bbox=dict(boxstyle="round", fc="0.9"),
            ha='center', va='center'
        )
        plt.annotate(
            'THE END ' + dates[-1],
            xy=(times[-1], 0),
            arrowprops=dict(arrowstyle='->'),
            xytext=(half, -0.5),
            bbox=dict(boxstyle="round", fc="0.9"),
            ha='center', va='center'
        )
        plt.annotate(
            'TRIUMPH ' + team1 + " " + triumph_times[team1][1],
            xy=( times[ triumph_times[team1][0] ], triumph_times[team1][2] /2 ),
            arrowprops=dict(arrowstyle='wedge',),
            xytext=(half, 0.5),
            bbox=dict(boxstyle="round", fc="0.9"),
            ha='center', va='center',
            size=20
        )
        plt.annotate(
            'TRIUMPH ' + team2 + " " + triumph_times[team2][1],
            xy=( times[ triumph_times[team2][0] ], triumph_times[team2][2] /2),
            arrowprops=dict(arrowstyle='wedge'),
            xytext=(half, 1.5),
            bbox=dict(boxstyle="round", fc="0.9"),
            ha='center', va='center',
            size=20
        )

        fig.savefig("KICKER_SCORES_GRAPH_DIFF.PNG", bbox_inches='tight')
        plt.legend()
        plt.show()


# variant1()
# variant2()

analyze_kicker_scores_plotly.py

import re
import json


j_file = open('/home/dmgl/Downloads/Telegram Desktop/ChatExport_2020-09-04/result.json', 'r')
j = json.load(j_file)

s_type = {'type': 'hashtag', 'text': '#scores'}

scores = [] # list of lists with score pairs [[5, 4], [5, 5], [5, 6], [7, 7], [8, 8], [9, 8], [9, 9], [10, 9], ...]
dates = [] # list of strings dates ['2017-09-04T20:25:41', '2017-09-05T18:18:35', '2017-09-05T20:42:58', ...]

for message in j['messages']:
    for text in message['text']:
        if text == s_type:
            date = message['date']
            # print(message)
            try:
                score = re.findall(r"[-+]?\d*\.\d+|\d+", message['text'][1])
                # print(message['text'])
                # print(date, score)
            except:
                pass

            scores.append(score)
            dates.append(date)

team1 = "GALOCHKIN, KLIMOV"
team2 = "OVCHAROV, STANOTIN"

times = [ d for d in range(len(dates)) ]
scores = [ [int(x[0]), int(x[1])] for x in scores ]

team1_scores = [ x[0] for x in scores ]
team2_scores = [ x[1] for x in scores ]

team1_scores_diff = []
team2_scores_diff = []
for s in scores:
    team1_scores_diff.append( (s[0]-s[1])/2 )
    team2_scores_diff.append( (s[1]-s[0])/2 )




import pandas as pd
import plotly.express as px
import plotly.graph_objects as go


# COUNT DATES HEATMAP

fig_heat = px.density_heatmap(dates, labels=dict(x='GAMES',y='DATES'), x=times, y=dates)

fig_heat.update_layout(title_text="COUNT DATES HEATMAP", title_font_size=20)
fig_heat.show()


# SUMMARY PROGRESS IN SCORES

x1 = dates
x2 = dates
y1 = team1_scores
y2 = team2_scores

df1 = pd.DataFrame.from_records([x1,y1])
df2 = pd.DataFrame.from_records([x2,y2])

fig_summary = go.Figure()

fig_summary.add_trace(go.Scatter(x=df1.values[0], y=df1.values[1],
                         name=team1, line_shape='linear',
                         showlegend=True,))
fig_summary.add_trace(go.Scatter(x=df2.values[0], y=df2.values[1],
                         name=team2, line_shape='linear',
                         showlegend=True,))

fig_summary.update_layout(title_text="SUMMARY PROGRESS IN SCORES", title_font_size=20)
fig_summary.show()


# DIFF BETWEEN TEAMS SCORES

x1 = dates
x2 = dates
y1 = team1_scores_diff
y2 = team2_scores_diff

df1 = pd.DataFrame.from_records([x1,y1])
df2 = pd.DataFrame.from_records([x2,y2])

fig_diff = go.Figure()

fig_diff.add_trace(go.Scatter(x=df1.values[0], y=df1.values[1],
                         name=team1, line_shape='spline',
                         showlegend=True,))
fig_diff.add_trace(go.Scatter(x=df2.values[0], y=df2.values[1],
                         name=team2, line_shape='spline',
                         showlegend=True,))

fig_diff.update_layout(title_text="DIFF BETWEEN TEAMS SCORES", title_font_size=20)
fig_diff.show()


# ANOTHER SUMMARY PROGRESS IN SCORES

x1 = times
x2 = times
y1 = team1_scores
y2 = team2_scores

df1 = pd.DataFrame.from_records([x1,y1])
df2 = pd.DataFrame.from_records([x2,y2])

fig_teams = go.Figure()
fig_teams.add_trace(go.Scatter(x=df1.values[0], y=df1.values[1],
                               name=team1, line_shape='hvh',
                               mode='lines+markers',
                               showlegend=True,
                               marker=dict(size=[x/5 for x in y1],color='darkgrey'),
                               ))
fig_teams.add_trace(go.Scatter(x=df2.values[0], y=df2.values[1],
                               name=team2, line_shape='hvh',
                               mode='lines+markers',
                               showlegend=True,
                               marker=dict(size=[x/5 for x in y2],color='lightgrey'),
                               ))

fig_teams.update_layout(barmode='overlay')
fig_teams.update_traces(opacity=0.9)

fig_teams.update_layout(title_text="ANOTHER SUMMARY PROGRESS IN SCORES", title_font_size=20)
fig_teams.show()


# BARS BY SCORES

fig_bars = go.Figure()
fig_bars.add_trace(go.Histogram(go.Histogram(x=team1_scores),name=team1,showlegend=True))
fig_bars.add_trace(go.Histogram(go.Histogram(x=team2_scores),name=team2,showlegend=True))

fig_bars.update_layout(title_text="SCORES BARS", title_font_size=20)
fig_bars.show()