pjk530

1клас пизже бабана

По итогу должно быть 3 числа для 3 сегментов или нет? да, я исправил уже

KeyError Traceback (most recent call last) Input In [1], in <cell line: 35>() 31 spisok[38;5;241m.[39mappend(cats [38;5;241m/[39m counter) 34 [38;5;28;01mimport[39;00m [38;5;21;01mseaborn[39;00m ---> 35 [43mseaborn[49m[38;5;241;43m.[39;49m[43mbarplot[49m[43m([49m[43mx[49m[38;5;241;43m=[39;49m[43m [49m[43mspisok[49m[43m,[49m[43m [49m[43my[49m[38;5;241;43m=[39;49m[43m [49m[43mspisok1[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/seaborn/_decorators.py:46, in _deprecate_positional_args.<locals>.inner_f(*args, **kwargs) 36 warnings[38;5;241m.[39mwarn( 37 [38;5;124m"[39m[38;5;124mPass the following variable[39m[38;5;132;01m{}[39;00m[38;5;124m as [39m[38;5;132;01m{}[39;00m[38;5;124mkeyword arg[39m[38;5;132;01m{}[39;00m[38;5;124m: [39m[38;5;132;01m{}[39;00m[38;5;124m. [39m[38;5;124m"[39m 38 [38;5;124m"[39m[38;5;124mFrom version 0.12, the only valid positional argument [39m[38;5;124m"[39m (...) 43 [38;5;167;01mFutureWarning[39;00m 44 ) 45 kwargs[38;5;241m.[39mupdate({k: arg [38;5;28;01mfor[39;00m k, arg [38;5;129;01min[39;00m [38;5;28mzip[39m(sig[38;5;241m.[39mparameters, args)}) ---> 46 [38;5;28;01mreturn[39;00m [43mf[49m[43m([49m[38;5;241;43m*[39;49m[38;5;241;43m*[39;49m[43mkwargs[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:3179, in barplot(x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, orient, color, palette, saturation, errcolor, errwidth, capsize, dodge, ax, **kwargs) 3166 [38;5;129m@_deprecate_positional_args[39m 3167 [38;5;28;01mdef[39;00m [38;5;21mbarplot[39m( 3168 [38;5;241m*[39m, (...) 3176 [38;5;241m*[39m[38;5;241m*[39mkwargs, 3177 ): -> 3179 plotter [38;5;241m=[39m [43m_BarPlotter[49m[43m([49m[43mx[49m[43m,[49m[43m [49m[43my[49m[43m,[49m[43m [49m[43mhue[49m[43m,[49m[43m [49m[43mdata[49m[43m,[49m[43m [49m[43morder[49m[43m,[49m[43m [49m[43mhue_order[49m[43m,[49m 3180 [43m [49m[43mestimator[49m[43m,[49m[43m [49m[43mci[49m[43m,[49m[43m [49m[43mn_boot[49m[43m,[49m[43m [49m[43munits[49m[43m,[49m[43m [49m[43mseed[49m[43m,[49m 3181 [43m [49m[43morient[49m[43m,[49m[43m [49m[43mcolor[49m[43m,[49m[43m [49m[43mpalette[49m[43m,[49m[43m [49m[43msaturation[49m[43m,[49m 3182 [43m [49m[43merrcolor[49m[43m,[49m[43m [49m[43merrwidth[49m[43m,[49m[43m [49m[43mcapsize[49m[43m,[49m[43m [49m[43mdodge[49m[43m)[49m 3184 [38;5;28;01mif[39;00m ax [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: 3185 ax [38;5;241m=[39m plt[38;5;241m.[39mgca() File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:1584, in _BarPlotter.__init__(self, x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, orient, color, palette, saturation, errcolor, errwidth, capsize, dodge) 1579 [38;5;28;01mdef[39;00m [38;5;21m__init__[39m([38;5;28mself[39m, x, y, hue, data, order, hue_order, 1580 estimator, ci, n_boot, units, seed, 1581 orient, color, palette, saturation, errcolor, 1582 errwidth, capsize, dodge): 1583 [38;5;124;03m"""Initialize the plotter."""[39;00m -> 1584 [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mestablish_variables[49m[43m([49m[43mx[49m[43m,[49m[43m [49m[43my[49m[43m,[49m[43m [49m[43mhue[49m[43m,[49m[43m [49m[43mdata[49m[43m,[49m[43m [49m[43morient[49m[43m,[49m 1585 [43m [49m[43morder[49m[43m,[49m[43m [49m[43mhue_order[49m[43m,[49m[43m [49m[43munits[49m[43m)[49m 1586 [38;5;28mself[39m[38;5;241m.[39mestablish_colors(color, palette, saturation) 1587 [38;5;28mself[39m[38;5;241m.[39mestimate_statistic(estimator, ci, n_boot, seed) File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:206, in _CategoricalPlotter.establish_variables(self, x, y, hue, data, orient, order, hue_order, units) 203 group_names [38;5;241m=[39m categorical_order(groups, order) 205 [38;5;66;03m# Group the numeric data[39;00m --> 206 plot_data, value_label [38;5;241m=[39m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_group_longform[49m[43m([49m[43mvals[49m[43m,[49m[43m [49m[43mgroups[49m[43m,[49m 207 [43m [49m[43mgroup_names[49m[43m)[49m 209 [38;5;66;03m# Now handle the hue levels for nested ordering[39;00m 210 [38;5;28;01mif[39;00m hue [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:253, in _CategoricalPlotter._group_longform(self, vals, grouper, order) 250 vals [38;5;241m=[39m pd[38;5;241m.[39mSeries(vals, index[38;5;241m=[39mindex) 252 [38;5;66;03m# Group the val data[39;00m --> 253 grouped_vals [38;5;241m=[39m [43mvals[49m[38;5;241;43m.[39;49m[43mgroupby[49m[43m([49m[43mgrouper[49m[43m)[49m 254 out_data [38;5;241m=[39m [] 255 [38;5;28;01mfor[39;00m g [38;5;129;01min[39;00m order: File /usr/local/lib/python3.9/site-packages/pandas/core/series.py:1720, in Series.groupby(self, by, axis, level, as_index, sort, group_keys, squeeze, observed, dropna) 1717 [38;5;28;01mraise[39;00m [38;5;167;01mTypeError[39;00m([38;5;124m"[39m[38;5;124mYou have to supply one of [39m[38;5;124m'[39m[38;5;124mby[39m[38;5;124m'[39m[38;5;124m and [39m[38;5;124m'[39m[38;5;124mlevel[39m[38;5;124m'[39m[38;5;124m"[39m) 1718 axis [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39m_get_axis_number(axis) -> 1720 [38;5;28;01mreturn[39;00m [43mSeriesGroupBy[49m[43m([49m 1721 [43m [49m[43mobj[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[43m,[49m 1722 [43m [49m[43mkeys[49m[38;5;241;43m=[39;49m[43mby[49m[43m,[49m 1723 [43m [49m[43maxis[49m[38;5;241;43m=[39;49m[43maxis[49m[43m,[49m 1724 [43m [49m[43mlevel[49m[38;5;241;43m=[39;49m[43mlevel[49m[43m,[49m 1725 [43m [49m[43mas_index[49m[38;5;241;43m=[39;49m[43mas_index[49m[43m,[49m 1726 [43m [49m[43msort[49m[38;5;241;43m=[39;49m[43msort[49m[43m,[49m 1727 [43m [49m[43mgroup_keys[49m[38;5;241;43m=[39;49m[43mgroup_keys[49m[43m,[49m 1728 [43m [49m[43msqueeze[49m[38;5;241;43m=[39;49m[43msqueeze[49m[43m,[49m 1729 [43m [49m[43mobserved[49m[38;5;241;43m=[39;49m[43mobserved[49m[43m,[49m 1730 [43m [49m[43mdropna[49m[38;5;241;43m=[39;49m[43mdropna[49m[43m,[49m 1731 [43m[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/pandas/core/groupby/groupby.py:560, in BaseGroupBy.__init__(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, squeeze, observed, mutated, dropna) 557 [38;5;28;01mif[39;00m grouper [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: 558 [38;5;28;01mfrom[39;00m [38;5;21;01mpandas[39;00m[38;5;21;01m.[39;00m[38;5;21;01mcore[39;00m[38;5;21;01m.[39;00m[38;5;21;01mgroupby[39;00m[38;5;21;01m.[39;00m[38;5;21;01mgrouper[39;00m [38;5;28;01mimport[39;00m get_grouper --> 560 grouper, exclusions, obj [38;5;241m=[39m [43mget_grouper[49m[43m([49m 561 [43m [49m[43mobj[49m[43m,[49m 562 [43m [49m[43mkeys[49m[43m,[49m 563 [43m [49m[43maxis[49m[38;5;241;43m=[39;49m[43maxis[49m[43m,[49m 564 [43m [49m[43mlevel[49m[38;5;241;43m=[39;49m[43mlevel[49m[43m,[49m 565 [43m [49m[43msort[49m[38;5;241;43m=[39;49m[43msort[49m[43m,[49m 566 [43m [49m[43mobserved[49m[38;5;241;43m=[39;49m[43mobserved[49m[43m,[49m 567 [43m [49m[43mmutated[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mmutated[49m[43m,[49m 568 [43m [49m[43mdropna[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mdropna[49m[43m,[49m 569 [43m [49m[43m)[49m 571 [38;5;28mself[39m[38;5;241m.[39mobj [38;5;241m=[39m obj 572 [38;5;28mself[39m[38;5;241m.[39maxis [38;5;241m=[39m obj[38;5;241m.[39m_get_axis_number(axis) File /usr/local/lib/python3.9/site-packages/pandas/core/groupby/grouper.py:811, in get_grouper(obj, key, axis, level, sort, observed, mutated, validate, dropna) 809 in_axis, name, level, gpr [38;5;241m=[39m [38;5;28;01mFalse[39;00m, [38;5;28;01mNone[39;00m, gpr, [38;5;28;01mNone[39;00m 810 [38;5;28;01melse[39;00m: --> 811 [38;5;28;01mraise[39;00m [38;5;167;01mKeyError[39;00m(gpr) 812 [38;5;28;01melif[39;00m [38;5;28misinstance[39m(gpr, Grouper) [38;5;129;01mand[39;00m gpr[38;5;241m.[39mkey [38;5;129;01mis[39;00m [38;5;129;01mnot[39;00m [38;5;28;01mNone[39;00m: 813 [38;5;66;03m# Add key to exclusions[39;00m 814 exclusions[38;5;241m.[39madd(gpr[38;5;241m.[39mkey) KeyError: 'Segment 0'

помогите с питоном, пожалуйста, не понимаю в чём ошибка. задание Соберите среднее количество робокотов по каждому сегменту из предыдущей задачи в один список. В другом списке перечислите названия сегментов через запятую: 'Segment 0', 'Segment 1', 'Segment 2'. Затем импортируйте seaborn и вызовите функцию barplot(), передав ей список со средними показателями как x и список с названиями сегментов как y. код import pandas import seaborn data = pandas.read_csv('support_data.csv') segment = list(data['segment']) robocats = list(data['robocats']) list0 = [] list1 = ['Segment 0', 'Segment 1', 'Segment 2'] cats = 0 counter = 0 for index in range(len(data)): if segment[index] == 'Segment 0': cats += robocats[index] counter += 1 list0.append(cats / counter) cats = 0 counter = 0 for index in range(len(data)): if segment[index] == 'Segment 1': cats += robocats[index] counter += 1 list0.append(cats / counter) cats = 0 counter = 0 for index in range(len(data)): if segment[index] == 'Segment 2': cats += robocats[index] counter += 1 list0.append(cats / counter) seaborn.barplot(x = list0, y = list1) ошибка --------------------------------------------------------------------------- KeyError Traceback (most recent call last) Input In [1], in <cell line: 30>() 28 counter [38;5;241m+[39m[38;5;241m=[39m [38;5;241m1[39m 29 list0[38;5;241m.[39mappend(cats [38;5;241m/[39m counter) ---> 30 [43mseaborn[49m[38;5;241;43m.[39;49m[43mbarplot[49m[43m([49m[43mx[49m[43m [49m[38;5;241;43m=[39;49m[43m [49m[43mlist0[49m[43m,[49m[43m [49m[43my[49m[43m [49m[38;5;241;43m=[39;49m[43m [49m[43mlist1[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/seaborn/_decorators.py:46, in _deprecate_positional_args.<locals>.inner_f(*args, **kwargs) 36 warnings[38;5;241m.[39mwarn( 37 [38;5;124m"[39m[38;5;124mPass the following variable[39m[38;5;132;01m{}[39;00m[38;5;124m as [39m[38;5;132;01m{}[39;00m[38;5;124mkeyword arg[39m[38;5;132;01m{}[39;00m[38;5;124m: [39m[38;5;132;01m{}[39;00m[38;5;124m. [39m[38;5;124m"[39m 38 [38;5;124m"[39m[38;5;124mFrom version 0.12, the only valid positional argument [39m[38;5;124m"[39m (...) 43 [38;5;167;01mFutureWarning[39;00m 44 ) 45 kwargs[38;5;241m.[39mupdate({k: arg [38;5;28;01mfor[39;00m k, arg [38;5;129;01min[39;00m [38;5;28mzip[39m(sig[38;5;241m.[39mparameters, args)}) ---> 46 [38;5;28;01mreturn[39;00m [43mf[49m[43m([49m[38;5;241;43m*[39;49m[38;5;241;43m*[39;49m[43mkwargs[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:3179, in barplot(x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, orient, color, palette, saturation, errcolor, errwidth, capsize, dodge, ax, **kwargs) 3166 [38;5;129m@_deprecate_positional_args[39m 3167 [38;5;28;01mdef[39;00m [38;5;21mbarplot[39m( 3168 [38;5;241m*[39m, (...) 3176 [38;5;241m*[39m[38;5;241m*[39mkwargs, 3177 ): -> 3179 plotter [38;5;241m=[39m [43m_BarPlotter[49m[43m([49m[43mx[49m[43m,[49m[43m [49m[43my[49m[43m,[49m[43m [49m[43mhue[49m[43m,[49m[43m [49m[43mdata[49m[43m,[49m[43m [49m[43morder[49m[43m,[49m[43m [49m[43mhue_order[49m[43m,[49m 3180 [43m [49m[43mestimator[49m[43m,[49m[43m [49m[43mci[49m[43m,[49m[43m [49m[43mn_boot[49m[43m,[49m[43m [49m[43munits[49m[43m,[49m[43m [49m[43mseed[49m[43m,[49m 3181 [43m [49m[43morient[49m[43m,[49m[43m [49m[43mcolor[49m[43m,[49m[43m [49m[43mpalette[49m[43m,[49m[43m [49m[43msaturation[49m[43m,[49m 3182 [43m [49m[43merrcolor[49m[43m,[49m[43m [49m[43merrwidth[49m[43m,[49m[43m [49m[43mcapsize[49m[43m,[49m[43m [49m[43mdodge[49m[43m)[49m 3184 [38;5;28;01mif[39;00m ax [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: 3185 ax [38;5;241m=[39m plt[38;5;241m.[39mgca() File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:1584, in _BarPlotter.__init__(self, x, y, hue, data, order, hue_order, estimator, ci, n_boot, units, seed, orient, color, palette, saturation, errcolor, errwidth, capsize, dodge) 1579 [38;5;28;01mdef[39;00m [38;5;21m__init__[39m([38;5;28mself[39m, x, y, hue, data, order, hue_order, 1580 estimator, ci, n_boot, units, seed, 1581 orient, color, palette, saturation, errcolor, 1582 errwidth, capsize, dodge): 1583 [38;5;124;03m"""Initialize the plotter."""[39;00m -> 1584 [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mestablish_variables[49m[43m([49m[43mx[49m[43m,[49m[43m [49m[43my[49m[43m,[49m[43m [49m[43mhue[49m[43m,[49m[43m [49m[43mdata[49m[43m,[49m[43m [49m[43morient[49m[43m,[49m 1585 [43m [49m[43morder[49m[43m,[49m[43m [49m[43mhue_order[49m[43m,[49m[43m [49m[43munits[49m[43m)[49m 1586 [38;5;28mself[39m[38;5;241m.[39mestablish_colors(color, palette, saturation) 1587 [38;5;28mself[39m[38;5;241m.[39mestimate_statistic(estimator, ci, n_boot, seed) File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:206, in _CategoricalPlotter.establish_variables(self, x, y, hue, data, orient, order, hue_order, units) 203 group_names [38;5;241m=[39m categorical_order(groups, order) 205 [38;5;66;03m# Group the numeric data[39;00m --> 206 plot_data, value_label [38;5;241m=[39m [38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43m_group_longform[49m[43m([49m[43mvals[49m[43m,[49m[43m [49m[43mgroups[49m[43m,[49m 207 [43m [49m[43mgroup_names[49m[43m)[49m 209 [38;5;66;03m# Now handle the hue levels for nested ordering[39;00m 210 [38;5;28;01mif[39;00m hue [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: File /usr/local/lib/python3.9/site-packages/seaborn/categorical.py:253, in _CategoricalPlotter._group_longform(self, vals, grouper, order) 250 vals [38;5;241m=[39m pd[38;5;241m.[39mSeries(vals, index[38;5;241m=[39mindex) 252 [38;5;66;03m# Group the val data[39;00m --> 253 grouped_vals [38;5;241m=[39m [43mvals[49m[38;5;241;43m.[39;49m[43mgroupby[49m[43m([49m[43mgrouper[49m[43m)[49m 254 out_data [38;5;241m=[39m [] 255 [38;5;28;01mfor[39;00m g [38;5;129;01min[39;00m order: File /usr/local/lib/python3.9/site-packages/pandas/core/series.py:1720, in Series.groupby(self, by, axis, level, as_index, sort, group_keys, squeeze, observed, dropna) 1717 [38;5;28;01mraise[39;00m [38;5;167;01mTypeError[39;00m([38;5;124m"[39m[38;5;124mYou have to supply one of [39m[38;5;124m'[39m[38;5;124mby[39m[38;5;124m'[39m[38;5;124m and [39m[38;5;124m'[39m[38;5;124mlevel[39m[38;5;124m'[39m[38;5;124m"[39m) 1718 axis [38;5;241m=[39m [38;5;28mself[39m[38;5;241m.[39m_get_axis_number(axis) -> 1720 [38;5;28;01mreturn[39;00m [43mSeriesGroupBy[49m[43m([49m 1721 [43m [49m[43mobj[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[43m,[49m 1722 [43m [49m[43mkeys[49m[38;5;241;43m=[39;49m[43mby[49m[43m,[49m 1723 [43m [49m[43maxis[49m[38;5;241;43m=[39;49m[43maxis[49m[43m,[49m 1724 [43m [49m[43mlevel[49m[38;5;241;43m=[39;49m[43mlevel[49m[43m,[49m 1725 [43m [49m[43mas_index[49m[38;5;241;43m=[39;49m[43mas_index[49m[43m,[49m 1726 [43m [49m[43msort[49m[38;5;241;43m=[39;49m[43msort[49m[43m,[49m 1727 [43m [49m[43mgroup_keys[49m[38;5;241;43m=[39;49m[43mgroup_keys[49m[43m,[49m 1728 [43m [49m[43msqueeze[49m[38;5;241;43m=[39;49m[43msqueeze[49m[43m,[49m 1729 [43m [49m[43mobserved[49m[38;5;241;43m=[39;49m[43mobserved[49m[43m,[49m 1730 [43m [49m[43mdropna[49m[38;5;241;43m=[39;49m[43mdropna[49m[43m,[49m 1731 [43m[49m[43m)[49m File /usr/local/lib/python3.9/site-packages/pandas/core/groupby/groupby.py:560, in BaseGroupBy.__init__(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, squeeze, observed, mutated, dropna) 557 [38;5;28;01mif[39;00m grouper [38;5;129;01mis[39;00m [38;5;28;01mNone[39;00m: 558 [38;5;28;01mfrom[39;00m [38;5;21;01mpandas[39;00m[38;5;21;01m.[39;00m[38;5;21;01mcore[39;00m[38;5;21;01m.[39;00m[38;5;21;01mgroupby[39;00m[38;5;21;01m.[39;00m[38;5;21;01mgrouper[39;00m [38;5;28;01mimport[39;00m get_grouper --> 560 grouper, exclusions, obj [38;5;241m=[39m [43mget_grouper[49m[43m([49m 561 [43m [49m[43mobj[49m[43m,[49m 562 [43m [49m[43mkeys[49m[43m,[49m 563 [43m [49m[43maxis[49m[38;5;241;43m=[39;49m[43maxis[49m[43m,[49m 564 [43m [49m[43mlevel[49m[38;5;241;43m=[39;49m[43mlevel[49m[43m,[49m 565 [43m [49m[43msort[49m[38;5;241;43m=[39;49m[43msort[49m[43m,[49m 566 [43m [49m[43mobserved[49m[38;5;241;43m=[39;49m[43mobserved[49m[43m,[49m 567 [43m [49m[43mmutated[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mmutated[49m[43m,[49m 568 [43m [49m[43mdropna[49m[38;5;241;43m=[39;49m[38;5;28;43mself[39;49m[38;5;241;43m.[39;49m[43mdropna[49m[43m,[49m 569 [43m [49m[43m)[49m 571 [38;5;28mself[39m[38;5;241m.[39mobj [38;5;241m=[39m obj 572 [38;5;28mself[39m[38;5;241m.[39maxis [38;5;241m=[39m obj[38;5;241m.[39m_get_axis_number(axis) File /usr/local/lib/python3.9/site-packages/pandas/core/groupby/grouper.py:811, in get_grouper(obj, key, axis, level, sort, observed, mutated, validate, dropna) 809 in_axis, name, level, gpr [38;5;241m=[39m [38;5;28;01mFalse[39;00m, [38;5;28;01mNone[39;00m, gpr, [38;5;28;01mNone[39;00m 810 [38;5;28;01melse[39;00m: --> 811 [38;5;28;01mraise[39;00m [38;5;167;01mKeyError[39;00m(gpr) 812 [38;5;28;01melif[39;00m [38;5;28misinstance[39m(gpr, Grouper) [38;5;129;01mand[39;00m gpr[38;5;241m.[39mkey [38;5;129;01mis[39;00m [38;5;129;01mnot[39;00m [38;5;28;01mNone[39;00m: 813 [38;5;66;03m# Add key to exclusions[39;00m 814 exclusions[38;5;241m.[39madd(gpr[38;5;241m.[39mkey) KeyError: 'Segment 0'

вот так должен был выглядеть рнб фристайл

я позволил тебе жить

у кого-то был баг при котором не назначается награда после убийств?

тебе срочно маму надо выебать свою