def similar_killer(champion_name): kill_matrix_adjacency = champion_matrix.sqlite_to_kill_matrix('picks').T # norm by picks; edge from column to row bibli_kill_matrix = kill_matrix_adjacency.T * kill_matrix_adjacency # bibliography kill matrix, bibli_kill temp_bibli_kill_ten = pd.DataFrame(bibli_kill_matrix.ix[champion_name]).sort(champion_name,ascending=False).iloc[0:10] plt_bibli_kill = temp_bibli_kill_ten.plot(kind='barh', title=champion_name + ' is similar with(TOP 10)', stacked=False).set_xlabel('Proportion').get_figure() plt_bibli_kill.savefig(champion_name + '_similar_killer.png')
def similar_killer(champion_name): kill_matrix_adjacency = lola.sqlite_to_kill_matrix('picks').T # norm by picks; edge from column to row bibli_kill_matrix = kill_matrix_adjacency.T * kill_matrix_adjacency # bibliography kill matrix, bibli_kill temp_bibli_kill_ten = pd.DataFrame(bibli_kill_matrix.ix[champion_name]).sort(champion_name,ascending=False).iloc[0:10] plt_bibli_kill = temp_bibli_kill_ten.plot(kind='barh', title=champion_name + ' is similar with(TOP 10)', stacked=False).set_xlabel('Proportion').get_figure() plt_bibli_kill.savefig(champion_name + '_similar_killer.png')
def similar_champions(champion_name): kill_matrix = champion_matrix.sqlite_to_kill_matrix('picks') # norm by picks kill_matrix_T = kill_matrix.T coci_kill_matrix = kill_matrix * kill_matrix_T # coci_kill temp_coci_kill_ten = pd.DataFrame(coci_kill_matrix.ix[champion_name]).sort(champion_name,ascending=False).iloc[0:10] plt_coci_kill = temp_coci_kill_ten.plot(kind='barh', title=champion_name + ' is similar with(TOP 10)', stacked=False).set_xlabel('Proportion').get_figure() plt_coci_kill.savefig(champion_name + '_similar.png')
def counter(champion_name): kill_matrix = champion_matrix.sqlite_to_kill_matrix('picks') # norm by picks temp_series = pd.DataFrame(kill_matrix.ix[champion_name]).sort(champion_name,ascending=False).iloc[0:10]#, ascending=False plttt = temp_series.plot(kind='barh', title='Top 10 choices to counter ' + champion_name, stacked=False).set_xlabel('Proportion').get_figure() plttt.savefig(champion_name +'_counter.png')
def counter(champion_name): kill_matrix = lola.sqlite_to_kill_matrix('picks') # norm by picks temp_series = pd.DataFrame(kill_matrix.ix[champion_name]).sort(champion_name,ascending=False).iloc[0:10]#, ascending=False plttt = temp_series.plot(kind='barh', title='Top 10 choices to counter ' + champion_name, stacked=False).set_xlabel('Proportion').get_figure() plttt.savefig(champion_name +'_counter.png')