# Poniendo las librerías from datetime import datetime import logging import numpy as np import pandas as pd import plotly.express as px import plotly.graph_objects as go import session_info

logging.basicConfig( format = '%(message)s', level=logging.DEBUG, encoding="utf-8" )

df = pd.read_csv('kcsep22.csv') logging.info(f'En total hay {df.shape[0]} usuarios registrados')

SELECT 'ZeroTG' AS Servers, SUM(CASE WHEN zerotg THEN 1 ELSE 0 END) AS Duelistas FROM df UNION ALL SELECT 'ZephraCarl' AS Servers, SUM(CASE WHEN zephra THEN 1 ELSE 0 END) AS Duelistas FROM df UNION ALL SELECT 'Bryan Norén' AS Servers, SUM(CASE WHEN bryan THEN 1 ELSE 0 END) AS Duelistas FROM df UNION ALL SELECT 'Xenoblur' AS Servers, SUM(CASE WHEN xenoblur THEN 1 ELSE 0 END) AS Duelistas FROM df;

comunidad = comunidad.sort_values('Duelistas', ascending=0) comunidad['Relación al Total'] = ( comunidad.Duelistas / df.shape[0] ).apply('{:.0%}'.format) fig = px.bar(comunidad, y='Duelistas', x="Servers", title="Registro de decks con su comunidad", text="Relación al Total", color="Servers", template="ggplot2") import plotly.graph_objects as go fig.add_indicator( mode="number", value=df.shape[0], title="Total de Duelistas", number={'font': {'size': 50}}, domain = {'x': [0.75, .95], 'y': [0.75, .95]}) fig.update_layout(showlegend=False) fig.show()

df['Día'] = pd.DatetimeIndex(df['ndmax']).day ndmax_fer_day = ( df.groupby(['Día'])['Día'].count() .reset_index(name='Duelistas')) fig = px.line( ndmax_fer_day, x="Día", y="Duelistas", title="Usuarios que llegan a NDmax por día", text="Duelistas", template='ggplot2') fig.update_yaxes(range=[0, 50]) fig.update_traces(textposition="top center") fig.show() logging.info(f'En promedio suelen tardar hasta el día {round(df.Día.mean())} para llegar a ndMAX')

resume = ( df.groupby(['deck','skill'])['skill'].size() .reset_index(name='total') .sort_values('total', ascending=0) ) meklord = resume.query("deck=='Meklord'") pecas = resume.query("deck=='Phantom Knights'") rose_dragon = resume.query("deck=='Rose Dragon'") galaxy_eyes = resume.query("deck=='Galaxy-Eyes'") e_heros = resume.query("deck=='Elemental Heros'") topfive=pd.concat([e_heros, galaxy_eyes, rose_dragon, pecas, meklord], ignore_index=True) fig = px.bar(topfive, y='deck', x="total", color="skill", title="Top Decks NDmax KC CUP Septiembre 2022", text="total", orientation='h', template="ggplot2") fig.update_layout(showlegend=False, xaxis_title="Total", yaxis_title="Decks") fig.show() logging.info(f'De {df["deck"].nunique()} arquetipos distintos este el top 5')

deck_variety_skill = ( df.groupby(['deck'])['skill'].nunique() .reset_index(name='total') .sort_values('total', ascending=0) ) deck_variety_skill.query("total>2")

logging.info('su lista de Habilidades del top 2') skill_df = resume.copy() skill_df["all"] = "su lista de Habilidades del top 2" fig = px.treemap( skill_df.query("deck=='Heros' or deck=='Magnet Warrios'"), path=['all', 'deck', 'skill'], values='total') fig.update_layout(title='Mazos con distintas Habilidades', title_x=0.5, margin = dict(t=50, l=25, r=25, b=25)) fig.show()

logging.info('Esta tabla representa la skill que se encuentra en distintos arquetipos') skill_distint_deck = ( df.groupby(['skill'])['deck'].nunique() .reset_index(name='total') .sort_values('total', ascending=0) ) skill_distint_deck.query("total>2")

logging.info('Tabla de todos los mazos que usan Robo del Destino') fig = px.treemap( skill_df.query("skill=='Robo del Destino'"), path=['skill', 'deck'], values='total') fig.update_layout( title='Tabla de todos los mazos que usan Robo del Destino', title_x=0.5, margin = dict(t=50, l=25, r=25, b=25) ) fig.show()

logging.info("Reporte finalizado")

# Actualizado a junio 2023 session_info.show()