<jupyter_start><jupyter_text>---  Знакомство<jupyter_code>plt.plot([1,2,3,2])
plt.plot([1,2,3,2], [4,3,2,1])
plt.hist(
    [0,0,1,2,2,2,2,3,3,4,5,6]
)<jupyter_output><empty_output><jupyter_text>---  Сбербанкhttps://www.kaggle.com/c/sberbank-russian-housing-market<jupyter_code>df = pd.read_csv('00_sberbank_macro.csv')
!cat data_dictionary.txt
df[~df['mortality'].isnull()]['mortality'].hist()
df['rent_price_1room_eco'].hist(bins=100)
tmp = df[[
    'timestamp', 'oil_urals', 'gdp_quart_growth'
]]
tmp['timestamp'] = pd.to_datetime(tmp['timestamp'])
tmp.set_index('timestamp').plot()
tmp.hist()
plt.plot(
    df[~df['gdp_quart'].isnull()]['gdp_quart'],
    df[~df['gdp_quart'].isnull()]['oil_urals'],
    '.'
)<jupyter_output><empty_output><jupyter_text>---  Вернемся к титанику<jupyter_code>df = pd.read_csv('00_titanic_train.csv')
fig, ax = plt.subplots(figsize=(20,10))
df.pivot_table('PassengerId', 'Pclass', 'Survived', 'count').plot(kind='bar', stacked=True, ax=ax)
fig, axes = plt.subplots(ncols=2)
train.pivot_table('PassengerId', ['SibSp'], 'Survived', 'count').plot(ax=axes[0], title='SibSp')
train.pivot_table('PassengerId', ['Parch'], 'Survived', 'count').plot(ax=axes[1], title='Parch')
df = df.drop(['Name', 'Ticket', 'Cabin'], axis=1)
df['Age'] = df['Age'].fillna(-1)
sns.pairplot(df, hue='Survived')<jupyter_output><empty_output>
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