2장_파이썬_기초문법_(2.13&14).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "02b09734",
   "metadata": {},
   "source": [
    "# 파이썬 패키지 사용하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5b4d1f5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn as sk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "02ad397d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__SKLEARN_SETUP__',\n",
       " '__all__',\n",
       " '__builtins__',\n",
       " '__cached__',\n",
       " '__check_build',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__path__',\n",
       " '__spec__',\n",
       " '__version__',\n",
       " '_config',\n",
       " '_distributor_init',\n",
       " 'base',\n",
       " 'clone',\n",
       " 'config_context',\n",
       " 'exceptions',\n",
       " 'externals',\n",
       " 'get_config',\n",
       " 'logger',\n",
       " 'logging',\n",
       " 'os',\n",
       " 'random',\n",
       " 'set_config',\n",
       " 'setup_module',\n",
       " 'show_versions',\n",
       " 'sys',\n",
       " 'utils']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(sk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e7083269",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "afa28560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['BooleanDtype',\n",
       " 'Categorical',\n",
       " 'CategoricalDtype',\n",
       " 'CategoricalIndex',\n",
       " 'DataFrame',\n",
       " 'DateOffset',\n",
       " 'DatetimeIndex',\n",
       " 'DatetimeTZDtype',\n",
       " 'ExcelFile',\n",
       " 'ExcelWriter',\n",
       " 'Flags',\n",
       " 'Float32Dtype',\n",
       " 'Float64Dtype',\n",
       " 'Float64Index',\n",
       " 'Grouper',\n",
       " 'HDFStore',\n",
       " 'Index',\n",
       " 'IndexSlice',\n",
       " 'Int16Dtype',\n",
       " 'Int32Dtype',\n",
       " 'Int64Dtype',\n",
       " 'Int64Index',\n",
       " 'Int8Dtype',\n",
       " 'Interval',\n",
       " 'IntervalDtype',\n",
       " 'IntervalIndex',\n",
       " 'MultiIndex',\n",
       " 'NA',\n",
       " 'NaT',\n",
       " 'NamedAgg',\n",
       " 'Period',\n",
       " 'PeriodDtype',\n",
       " 'PeriodIndex',\n",
       " 'RangeIndex',\n",
       " 'Series',\n",
       " 'SparseDtype',\n",
       " 'StringDtype',\n",
       " 'Timedelta',\n",
       " 'TimedeltaIndex',\n",
       " 'Timestamp',\n",
       " 'UInt16Dtype',\n",
       " 'UInt32Dtype',\n",
       " 'UInt64Dtype',\n",
       " 'UInt64Index',\n",
       " 'UInt8Dtype',\n",
       " '__builtins__',\n",
       " '__cached__',\n",
       " '__doc__',\n",
       " '__docformat__',\n",
       " '__file__',\n",
       " '__getattr__',\n",
       " '__git_version__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__path__',\n",
       " '__spec__',\n",
       " '__version__',\n",
       " '_config',\n",
       " '_hashtable',\n",
       " '_is_numpy_dev',\n",
       " '_lib',\n",
       " '_libs',\n",
       " '_np_version_under1p18',\n",
       " '_testing',\n",
       " '_tslib',\n",
       " '_typing',\n",
       " '_version',\n",
       " 'api',\n",
       " 'array',\n",
       " 'arrays',\n",
       " 'bdate_range',\n",
       " 'compat',\n",
       " 'concat',\n",
       " 'core',\n",
       " 'crosstab',\n",
       " 'cut',\n",
       " 'date_range',\n",
       " 'describe_option',\n",
       " 'errors',\n",
       " 'eval',\n",
       " 'factorize',\n",
       " 'get_dummies',\n",
       " 'get_option',\n",
       " 'infer_freq',\n",
       " 'interval_range',\n",
       " 'io',\n",
       " 'isna',\n",
       " 'isnull',\n",
       " 'json_normalize',\n",
       " 'lreshape',\n",
       " 'melt',\n",
       " 'merge',\n",
       " 'merge_asof',\n",
       " 'merge_ordered',\n",
       " 'notna',\n",
       " 'notnull',\n",
       " 'offsets',\n",
       " 'option_context',\n",
       " 'options',\n",
       " 'pandas',\n",
       " 'period_range',\n",
       " 'pivot',\n",
       " 'pivot_table',\n",
       " 'plotting',\n",
       " 'qcut',\n",
       " 'read_clipboard',\n",
       " 'read_csv',\n",
       " 'read_excel',\n",
       " 'read_feather',\n",
       " 'read_fwf',\n",
       " 'read_gbq',\n",
       " 'read_hdf',\n",
       " 'read_html',\n",
       " 'read_json',\n",
       " 'read_orc',\n",
       " 'read_parquet',\n",
       " 'read_pickle',\n",
       " 'read_sas',\n",
       " 'read_spss',\n",
       " 'read_sql',\n",
       " 'read_sql_query',\n",
       " 'read_sql_table',\n",
       " 'read_stata',\n",
       " 'read_table',\n",
       " 'read_xml',\n",
       " 'reset_option',\n",
       " 'set_eng_float_format',\n",
       " 'set_option',\n",
       " 'show_versions',\n",
       " 'test',\n",
       " 'testing',\n",
       " 'timedelta_range',\n",
       " 'to_datetime',\n",
       " 'to_numeric',\n",
       " 'to_pickle',\n",
       " 'to_timedelta',\n",
       " 'tseries',\n",
       " 'unique',\n",
       " 'util',\n",
       " 'value_counts',\n",
       " 'wide_to_long']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(pd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e831a6c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6af7c5d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ALLOW_THREADS',\n",
       " 'AxisError',\n",
       " 'BUFSIZE',\n",
       " 'Bytes0',\n",
       " 'CLIP',\n",
       " 'ComplexWarning',\n",
       " 'DataSource',\n",
       " 'Datetime64',\n",
       " 'ERR_CALL',\n",
       " 'ERR_DEFAULT',\n",
       " 'ERR_IGNORE',\n",
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       " 'ERR_WARN',\n",
       " 'FLOATING_POINT_SUPPORT',\n",
       " 'FPE_DIVIDEBYZERO',\n",
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       " 'FPE_OVERFLOW',\n",
       " 'FPE_UNDERFLOW',\n",
       " 'False_',\n",
       " 'Inf',\n",
       " 'Infinity',\n",
       " 'MAXDIMS',\n",
       " 'MAY_SHARE_BOUNDS',\n",
       " 'MAY_SHARE_EXACT',\n",
       " 'MachAr',\n",
       " 'ModuleDeprecationWarning',\n",
       " 'NAN',\n",
       " 'NINF',\n",
       " 'NZERO',\n",
       " 'NaN',\n",
       " 'PINF',\n",
       " 'PZERO',\n",
       " 'RAISE',\n",
       " 'RankWarning',\n",
       " 'SHIFT_DIVIDEBYZERO',\n",
       " 'SHIFT_INVALID',\n",
       " 'SHIFT_OVERFLOW',\n",
       " 'SHIFT_UNDERFLOW',\n",
       " 'ScalarType',\n",
       " 'Str0',\n",
       " 'Tester',\n",
       " 'TooHardError',\n",
       " 'True_',\n",
       " 'UFUNC_BUFSIZE_DEFAULT',\n",
       " 'UFUNC_PYVALS_NAME',\n",
       " 'Uint64',\n",
       " 'VisibleDeprecationWarning',\n",
       " 'WRAP',\n",
       " '_NoValue',\n",
       " '_UFUNC_API',\n",
       " '__NUMPY_SETUP__',\n",
       " '__all__',\n",
       " '__builtins__',\n",
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       " '_financial_names',\n",
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       " 'arcsin',\n",
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       " 'sort',\n",
       " 'sort_complex',\n",
       " 'source',\n",
       " 'spacing',\n",
       " 'split',\n",
       " 'sqrt',\n",
       " 'square',\n",
       " 'squeeze',\n",
       " 'stack',\n",
       " 'std',\n",
       " 'str0',\n",
       " 'str_',\n",
       " 'string_',\n",
       " 'subtract',\n",
       " 'sum',\n",
       " 'swapaxes',\n",
       " 'sys',\n",
       " 'take',\n",
       " 'take_along_axis',\n",
       " 'tan',\n",
       " 'tanh',\n",
       " 'tensordot',\n",
       " 'test',\n",
       " 'testing',\n",
       " 'tile',\n",
       " 'timedelta64',\n",
       " 'trace',\n",
       " 'tracemalloc_domain',\n",
       " 'transpose',\n",
       " 'trapz',\n",
       " 'tri',\n",
       " 'tril',\n",
       " 'tril_indices',\n",
       " 'tril_indices_from',\n",
       " 'trim_zeros',\n",
       " 'triu',\n",
       " 'triu_indices',\n",
       " 'triu_indices_from',\n",
       " 'true_divide',\n",
       " 'trunc',\n",
       " 'typecodes',\n",
       " 'typename',\n",
       " 'ubyte',\n",
       " 'ufunc',\n",
       " 'uint',\n",
       " 'uint0',\n",
       " 'uint16',\n",
       " 'uint32',\n",
       " 'uint64',\n",
       " 'uint8',\n",
       " 'uintc',\n",
       " 'uintp',\n",
       " 'ulonglong',\n",
       " 'unicode_',\n",
       " 'union1d',\n",
       " 'unique',\n",
       " 'unpackbits',\n",
       " 'unravel_index',\n",
       " 'unsignedinteger',\n",
       " 'unwrap',\n",
       " 'use_hugepage',\n",
       " 'ushort',\n",
       " 'vander',\n",
       " 'var',\n",
       " 'vdot',\n",
       " 'vectorize',\n",
       " 'version',\n",
       " 'void',\n",
       " 'void0',\n",
       " 'vsplit',\n",
       " 'vstack',\n",
       " 'warnings',\n",
       " 'where',\n",
       " 'who',\n",
       " 'zeros',\n",
       " 'zeros_like']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ed5b5a90",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn.preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e986367d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Binarizer',\n",
       " 'FunctionTransformer',\n",
       " 'KBinsDiscretizer',\n",
       " 'KernelCenterer',\n",
       " 'LabelBinarizer',\n",
       " 'LabelEncoder',\n",
       " 'MaxAbsScaler',\n",
       " 'MinMaxScaler',\n",
       " 'MultiLabelBinarizer',\n",
       " 'Normalizer',\n",
       " 'OneHotEncoder',\n",
       " 'OrdinalEncoder',\n",
       " 'PolynomialFeatures',\n",
       " 'PowerTransformer',\n",
       " 'QuantileTransformer',\n",
       " 'RobustScaler',\n",
       " 'SplineTransformer',\n",
       " 'StandardScaler',\n",
       " '__all__',\n",
       " '__builtins__',\n",
       " '__cached__',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__path__',\n",
       " '__spec__',\n",
       " '_csr_polynomial_expansion',\n",
       " '_data',\n",
       " '_discretization',\n",
       " '_encoders',\n",
       " '_function_transformer',\n",
       " '_label',\n",
       " '_polynomial',\n",
       " 'add_dummy_feature',\n",
       " 'binarize',\n",
       " 'label_binarize',\n",
       " 'maxabs_scale',\n",
       " 'minmax_scale',\n",
       " 'normalize',\n",
       " 'power_transform',\n",
       " 'quantile_transform',\n",
       " 'robust_scale',\n",
       " 'scale']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(sklearn.preprocessing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c9d15495",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.arange(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3f69ca8",
   "metadata": {},
   "source": [
    "# 파이썬의 자료형"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4221b9b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sys import getsizeof"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e0d9b2dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = 1\n",
    "getsizeof(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1a55f0be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = 1.0\n",
    "getsizeof(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "73dc8534",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = \"1\"\n",
    "getsizeof(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fccfc7d2",
   "metadata": {},
   "source": [
    "파이썬에서 사용할 수 있는 자료형 중 많이 사용하는 것은 다음과 같다.\n",
    "\n",
    "* NoneType\n",
    "\n",
    "* bool\n",
    "\n",
    "* int\n",
    "\n",
    "* float\n",
    "\n",
    "* complex\n",
    "\n",
    "* str\n",
    "\n",
    "* tuple\n",
    "\n",
    "* list\n",
    "\n",
    "* dict\n",
    "\n",
    "* function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "619dcb83",
   "metadata": {},
   "outputs": [],
   "source": [
    "b = [1, 2, 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1f3a2eae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5b7cc2bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.__class__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "de0f6bd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "today = \"2020-10-25\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7dbaf0e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20201025"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "today = today.replace(\"-\",\"\")\n",
    "int(today)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1847da57",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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