Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pandas import Series, DataFrame\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "obj = Series([1, -2, -3, 4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1   -2\n",
       "2   -3\n",
       "3    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1, -2, -3,  4], dtype=int64)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=4, step=1)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "obj2 = Series([5, 3, -1, 4], index=['a', 'b', 'c', 'd'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['a', 'b', 'c', 'd'], dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj2.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj2[\"b\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    5\n",
       "b    3\n",
       "d    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj2[obj2 > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = {\"A\" : [\"a\", \"b\", \"c\", \"d\", \"e\"],\n",
    "\"B\" : [1, 2, 3, 4, 5],\n",
    "\"C\" : [1.2, 1.4, 5.4, 2.2, 4.3]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'A': ['a', 'b', 'c', 'd', 'e'],\n",
       " 'B': [1, 2, 3, 4, 5],\n",
       " 'C': [1.2, 1.4, 5.4, 2.2, 4.3]}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame = DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d</td>\n",
       "      <td>4</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B    C\n",
       "0  a  1  1.2\n",
       "1  b  2  1.4\n",
       "2  c  3  5.4\n",
       "3  d  4  2.2\n",
       "4  e  5  4.3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
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       "</table>\n",
       "</div>"
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      "text/plain": [
       "   A  B\n",
       "0  a  1\n",
       "1  b  2\n",
       "2  c  3\n",
       "3  d  4\n",
       "4  e  5"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame[[\"A\", \"B\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame[\"D\"] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>1.2</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
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       "      <td>5.4</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B    C  D\n",
       "0  a  1  1.2  0\n",
       "1  b  2  1.4  0\n",
       "2  c  3  5.4  0\n",
       "3  d  4  2.2  0\n",
       "4  e  5  4.3  0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = {\"A\" : [\"a\", \"b\", \"c\", \"d\", \"e\"],\n",
    "\"B\" : [1, 2, 3, 4, 5],\n",
    "\"C\" : [1.2, 1.4, 5.4, 2.2, 4.3]}\n",
    "frame = DataFrame(data, index= [\"one\", \"two\", \"three\", \"four\", \"five\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>c</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>d</td>\n",
       "      <td>4</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A  B    C\n",
       "one    a  1  1.2\n",
       "two    b  2  1.4\n",
       "three  c  3  5.4\n",
       "four   d  4  2.2\n",
       "five   e  5  4.3"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead tr:only-child th {\n",
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       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>c</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A  B    C\n",
       "two    b  2  1.4\n",
       "three  c  3  5.4\n",
       "five   e  5  4.3"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.drop([\"one\", \"four\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>C</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>a</td>\n",
       "      <td>1.2</td>\n",
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       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>b</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>c</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>d</td>\n",
       "      <td>2.2</td>\n",
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       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>e</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "       A    C\n",
       "one    a  1.2\n",
       "two    b  1.4\n",
       "three  c  5.4\n",
       "four   d  2.2\n",
       "five   e  4.3"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.drop([\"B\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>c</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>d</td>\n",
       "      <td>4</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A  B    C\n",
       "one    a  1  1.2\n",
       "two    b  2  1.4\n",
       "three  c  3  5.4\n",
       "four   d  4  2.2\n",
       "five   e  5  4.3"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>d</td>\n",
       "      <td>4</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>e</td>\n",
       "      <td>5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      A  B    C\n",
       "four  d  4  2.2\n",
       "five  e  5  4.3"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame[(frame[\"C\"] > 2) & (frame[\"B\"] > 3)]"
   ]
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  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B      1\n",
       "C    1.2\n",
       "Name: one, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.ix[\"one\", [\"B\", \"C\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
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       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>4</td>\n",
       "      <td>2.2</td>\n",
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       "</table>\n",
       "</div>"
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      "text/plain": [
       "      B    C\n",
       "one   1  1.2\n",
       "four  4  2.2"
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     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
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    "frame.ix[[\"one\", \"four\"], [\"B\", \"C\"]]"
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  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame = DataFrame(np.random.rand(4, 3), columns=list(\"ABC\"),\n",
    "index=list(\"abcd\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
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       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0.811886</td>\n",
       "      <td>0.944423</td>\n",
       "      <td>0.405110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>0.530458</td>\n",
       "      <td>0.158157</td>\n",
       "      <td>0.116286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.434140</td>\n",
       "      <td>0.884494</td>\n",
       "      <td>0.777189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.006149</td>\n",
       "      <td>0.016096</td>\n",
       "      <td>0.886616</td>\n",
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      "text/plain": [
       "          A         B         C\n",
       "a  0.811886  0.944423  0.405110\n",
       "b  0.530458  0.158157  0.116286\n",
       "c  0.434140  0.884494  0.777189\n",
       "d  0.006149  0.016096  0.886616"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.811886\n",
       "B    0.944423\n",
       "C    0.886616\n",
       "dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.apply(max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    2.161419\n",
       "b    0.804901\n",
       "c    2.095823\n",
       "d    0.908861\n",
       "dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.apply(sum, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_2(x):\n",
    "    return x + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
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       "      <th>b</th>\n",
       "      <td>2.530458</td>\n",
       "      <td>2.158157</td>\n",
       "      <td>2.116286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>2.434140</td>\n",
       "      <td>2.884494</td>\n",
       "      <td>2.777189</td>\n",
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       "    <tr>\n",
       "      <th>d</th>\n",
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      "text/plain": [
       "          A         B         C\n",
       "a  2.811886  2.944423  2.405110\n",
       "b  2.530458  2.158157  2.116286\n",
       "c  2.434140  2.884494  2.777189\n",
       "d  2.006149  2.016096  2.886616"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "frame.applymap(add_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    2.811886\n",
       "b    2.530458\n",
       "c    2.434140\n",
       "d    2.006149\n",
       "Name: A, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['A'].map(add_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead tr:only-child th {\n",
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       "    .dataframe thead th {\n",
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       "      <th>a</th>\n",
       "      <td>2.944423</td>\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>2.158157</td>\n",
       "      <td>2.116286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>2.884494</td>\n",
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       "      <th>d</th>\n",
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      "text/plain": [
       "          B         C\n",
       "a  2.944423  2.405110\n",
       "b  2.158157  2.116286\n",
       "c  2.884494  2.777189\n",
       "d  2.016096  2.886616"
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     "metadata": {},
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    "frame.ix[:, [\"B\", \"C\"]].applymap(add_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
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       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.445658</td>\n",
       "      <td>0.500792</td>\n",
       "      <td>0.546300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.333974</td>\n",
       "      <td>0.481790</td>\n",
       "      <td>0.353068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.006149</td>\n",
       "      <td>0.016096</td>\n",
       "      <td>0.116286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.327142</td>\n",
       "      <td>0.122642</td>\n",
       "      <td>0.332904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.482299</td>\n",
       "      <td>0.521326</td>\n",
       "      <td>0.591150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.600815</td>\n",
       "      <td>0.899477</td>\n",
       "      <td>0.804546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.811886</td>\n",
       "      <td>0.944423</td>\n",
       "      <td>0.886616</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              A         B         C\n",
       "count  4.000000  4.000000  4.000000\n",
       "mean   0.445658  0.500792  0.546300\n",
       "std    0.333974  0.481790  0.353068\n",
       "min    0.006149  0.016096  0.116286\n",
       "25%    0.327142  0.122642  0.332904\n",
       "50%    0.482299  0.521326  0.591150\n",
       "75%    0.600815  0.899477  0.804546\n",
       "max    0.811886  0.944423  0.886616"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "obj = Series(['c', 'a', 'c', 'a', 'b', 'b', 'c'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "c    3\n",
       "a    2\n",
       "b    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_frame = DataFrame([[1, 2, 3],\n",
    "[1, np.nan, np.nan],\n",
    "[np.nan, np.nan, np.nan],\n",
    "[np.nan, 6.5, 3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "     0    1    2\n",
       "0  1.0  2.0  3.0\n",
       "1  1.0  NaN  NaN\n",
       "2  NaN  NaN  NaN\n",
       "3  NaN  6.5  3.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame"
   ]
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  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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      "text/plain": [
       "     0    1    2\n",
       "0  1.0  2.0  3.0"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0    1    2\n",
       "0  1.0  2.0  3.0\n",
       "1  1.0  NaN  NaN\n",
       "3  NaN  6.5  3.0"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame.dropna(how=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from numpy.random import randn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
    "y = [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7190bf0>]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uvnlfcc7NdM5lOOcyEhISmimGiIg0V9FnAv3NrLeZRQE3AIuaaV0iIvItmuUY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\nU9GLiIQ4Fb2ISIhT0YuIhDgVvYhIiPs/znb3iL+1s+0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7010810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "receipt_data = pd.read_excel(\"김상묵의영수증.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>날짜</th>\n",
       "      <th>자산</th>\n",
       "      <th>분류</th>\n",
       "      <th>소분류</th>\n",
       "      <th>내용</th>\n",
       "      <th>KRW</th>\n",
       "      <th>수입/지출</th>\n",
       "      <th>메모</th>\n",
       "      <th>금액</th>\n",
       "      <th>화폐</th>\n",
       "      <th>자산.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>강변마트</td>\n",
       "      <td>2300</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2300</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>써브웨이대전</td>\n",
       "      <td>4500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>700</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700</td>\n",
       "      <td>KRW</td>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>간식</td>\n",
       "      <td>던킨도너츠대</td>\n",
       "      <td>1872</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1872</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3550</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3550</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>경조사/회비</td>\n",
       "      <td>선물</td>\n",
       "      <td>카카오</td>\n",
       "      <td>4100</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4100</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>700</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700</td>\n",
       "      <td>KRW</td>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>롯데마켓999</td>\n",
       "      <td>3680</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3680</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>간식</td>\n",
       "      <td>던킨도너츠대</td>\n",
       "      <td>3666</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3666</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>(주)아워홈</td>\n",
       "      <td>1300</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1300</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>(주)신세계</td>\n",
       "      <td>4000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>4000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>700</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700</td>\n",
       "      <td>KRW</td>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>강변마트</td>\n",
       "      <td>4250</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4250</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>패션/미용</td>\n",
       "      <td>패션잡화</td>\n",
       "      <td>쿠팡</td>\n",
       "      <td>312760</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>312760</td>\n",
       "      <td>KRW</td>\n",
       "      <td>312760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>음료</td>\n",
       "      <td>그린브라우니</td>\n",
       "      <td>3500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>1117meal</td>\n",
       "      <td>10400</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10400</td>\n",
       "      <td>KRW</td>\n",
       "      <td>10400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>간식</td>\n",
       "      <td>던킨도너츠대</td>\n",
       "      <td>2028</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2028</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>고봉민김밥인</td>\n",
       "      <td>7000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>커피살림</td>\n",
       "      <td>4000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>NICE_배달의</td>\n",
       "      <td>20600</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20600</td>\n",
       "      <td>KRW</td>\n",
       "      <td>20600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2018-01-26</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>NICE_배달의</td>\n",
       "      <td>16000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>강변마트</td>\n",
       "      <td>5200</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5200</td>\n",
       "      <td>KRW</td>\n",
       "      <td>5200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>커피니어은점</td>\n",
       "      <td>2800</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2800</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>NICE_배달의</td>\n",
       "      <td>13000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2018-01-06</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>강변마트</td>\n",
       "      <td>2100</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2100</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>생활용품</td>\n",
       "      <td>가구/가전</td>\n",
       "      <td>이불</td>\n",
       "      <td>83480</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83480</td>\n",
       "      <td>KRW</td>\n",
       "      <td>83480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>700</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>700</td>\n",
       "      <td>KRW</td>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>주거/통신</td>\n",
       "      <td>공과금</td>\n",
       "      <td>Toss한전</td>\n",
       "      <td>7670</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7670</td>\n",
       "      <td>KRW</td>\n",
       "      <td>7670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>주거/통신</td>\n",
       "      <td>공과금</td>\n",
       "      <td>Toss씨엔씨티</td>\n",
       "      <td>82180</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82180</td>\n",
       "      <td>KRW</td>\n",
       "      <td>82180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>주거/통신</td>\n",
       "      <td>관리비</td>\n",
       "      <td>Toss홍종호</td>\n",
       "      <td>20000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>한우국밥</td>\n",
       "      <td>5000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>교통/차량</td>\n",
       "      <td>대중교통</td>\n",
       "      <td>교통대금결제</td>\n",
       "      <td>4320</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4320</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>2850</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2850</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>1700</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1700</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>페퍼스레스토</td>\n",
       "      <td>5500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>5500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>카이스트망고</td>\n",
       "      <td>2000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>2650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>주신일과</td>\n",
       "      <td>1800</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1800</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>강변마트</td>\n",
       "      <td>1000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>3650</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3650</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>간식</td>\n",
       "      <td>도너츠</td>\n",
       "      <td>1170</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1170</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>식사</td>\n",
       "      <td>삼성웰스토리</td>\n",
       "      <td>2350</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2350</td>\n",
       "      <td>KRW</td>\n",
       "      <td>2350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>야식</td>\n",
       "      <td>교촌치킨만년</td>\n",
       "      <td>15000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>간식</td>\n",
       "      <td>코레일유통</td>\n",
       "      <td>1500</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1500</td>\n",
       "      <td>KRW</td>\n",
       "      <td>1500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>엔제리너스서</td>\n",
       "      <td>4600</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4600</td>\n",
       "      <td>KRW</td>\n",
       "      <td>4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>식비</td>\n",
       "      <td>커피</td>\n",
       "      <td>샵52랩</td>\n",
       "      <td>3000</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3000</td>\n",
       "      <td>KRW</td>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>[KB]</td>\n",
       "      <td>생활용품</td>\n",
       "      <td>잡화소모</td>\n",
       "      <td>노트, 양말</td>\n",
       "      <td>17520</td>\n",
       "      <td>지출</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17520</td>\n",
       "      <td>KRW</td>\n",
       "      <td>17520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            날짜    자산      분류    소분류        내용     KRW 수입/지출  메모      금액   화폐  \\\n",
       "0   2018-01-31  [KB]      식비     야식      강변마트    2300    지출 NaN    2300  KRW   \n",
       "1   2018-01-31  [KB]      식비     식사    써브웨이대전    4500    지출 NaN    4500  KRW   \n",
       "2   2018-01-31  [KB]      식비     커피    카이스트망고    2000    지출 NaN    2000  KRW   \n",
       "3   2018-01-31  [KB]      식비     식사    삼성웰스토리    3500    지출 NaN    3500  KRW   \n",
       "4   2018-01-31  [KB]      식비     식사      주신일과     700    지출 NaN     700  KRW   \n",
       "5   2018-01-30  [KB]      식비     간식    던킨도너츠대    1872    지출 NaN    1872  KRW   \n",
       "6   2018-01-30  [KB]      식비     식사    삼성웰스토리    3650    지출 NaN    3650  KRW   \n",
       "7   2018-01-30  [KB]      식비     커피    카이스트망고    2000    지출 NaN    2000  KRW   \n",
       "8   2018-01-30  [KB]      식비     식사    삼성웰스토리    3550    지출 NaN    3550  KRW   \n",
       "9   2018-01-30  [KB]  경조사/회비     선물       카카오    4100    지출 NaN    4100  KRW   \n",
       "10  2018-01-30  [KB]      식비     식사      주신일과     700    지출 NaN     700  KRW   \n",
       "11  2018-01-29  [KB]      식비     야식   롯데마켓999    3680    지출 NaN    3680  KRW   \n",
       "12  2018-01-29  [KB]      식비     간식    던킨도너츠대    3666    지출 NaN    3666  KRW   \n",
       "13  2018-01-29  [KB]      식비     커피    (주)아워홈    1300    지출 NaN    1300  KRW   \n",
       "14  2018-01-29  [KB]      식비     식사    (주)신세계    4000    지출 NaN    4000  KRW   \n",
       "15  2018-01-29  [KB]      식비     커피    카이스트망고    2500    지출 NaN    2500  KRW   \n",
       "16  2018-01-29  [KB]      식비     식사    삼성웰스토리    4000    지출 NaN    4000  KRW   \n",
       "17  2018-01-29  [KB]      식비     식사      주신일과     700    지출 NaN     700  KRW   \n",
       "18  2018-01-28  [KB]      식비     야식      강변마트    4250    지출 NaN    4250  KRW   \n",
       "19  2018-01-28  [KB]   패션/미용   패션잡화        쿠팡  312760    지출 NaN  312760  KRW   \n",
       "20  2018-01-28  [KB]      식비     음료    그린브라우니    3500    지출 NaN    3500  KRW   \n",
       "21  2018-01-28  [KB]      식비     식사  1117meal   10400    지출 NaN   10400  KRW   \n",
       "22  2018-01-28  [KB]      식비     간식    던킨도너츠대    2028    지출 NaN    2028  KRW   \n",
       "23  2018-01-28  [KB]      식비     커피    카이스트망고    2500    지출 NaN    2500  KRW   \n",
       "24  2018-01-28  [KB]      식비     식사    고봉민김밥인    7000    지출 NaN    7000  KRW   \n",
       "25  2018-01-27  [KB]      식비     커피      커피살림    4000    지출 NaN    4000  KRW   \n",
       "26  2018-01-27  [KB]      식비     식사  NICE_배달의   20600    지출 NaN   20600  KRW   \n",
       "27  2018-01-27  [KB]      식비     커피    카이스트망고    2000    지출 NaN    2000  KRW   \n",
       "28  2018-01-27  [KB]      식비     식사    삼성웰스토리    3650    지출 NaN    3650  KRW   \n",
       "29  2018-01-26  [KB]      식비     식사  NICE_배달의   16000    지출 NaN   16000  KRW   \n",
       "..         ...   ...     ...    ...       ...     ...   ...  ..     ...  ...   \n",
       "128 2018-01-07  [KB]      식비     커피    카이스트망고    2500    지출 NaN    2500  KRW   \n",
       "129 2018-01-07  [KB]      식비     식사    삼성웰스토리    3650    지출 NaN    3650  KRW   \n",
       "130 2018-01-06  [KB]      식비     야식      강변마트    5200    지출 NaN    5200  KRW   \n",
       "131 2018-01-06  [KB]      식비     커피    커피니어은점    2800    지출 NaN    2800  KRW   \n",
       "132 2018-01-06  [KB]      식비     식사  NICE_배달의   13000    지출 NaN   13000  KRW   \n",
       "133 2018-01-06  [KB]      식비     커피    카이스트망고    2500    지출 NaN    2500  KRW   \n",
       "134 2018-01-06  [KB]      식비     식사    삼성웰스토리    3650    지출 NaN    3650  KRW   \n",
       "135 2018-01-05  [KB]      식비     야식      강변마트    2100    지출 NaN    2100  KRW   \n",
       "136 2018-01-05  [KB]    생활용품  가구/가전        이불   83480    지출 NaN   83480  KRW   \n",
       "137 2018-01-05  [KB]      식비     식사      주신일과     700    지출 NaN     700  KRW   \n",
       "138 2018-01-04  [KB]   주거/통신    공과금    Toss한전    7670    지출 NaN    7670  KRW   \n",
       "139 2018-01-04  [KB]   주거/통신    공과금  Toss씨엔씨티   82180    지출 NaN   82180  KRW   \n",
       "140 2018-01-04  [KB]   주거/통신    관리비   Toss홍종호   20000    지출 NaN   20000  KRW   \n",
       "141 2018-01-04  [KB]      식비     식사      한우국밥    5000    지출 NaN    5000  KRW   \n",
       "142 2018-01-04  [KB]   교통/차량   대중교통    교통대금결제    4320    지출 NaN    4320  KRW   \n",
       "143 2018-01-04  [KB]      식비     식사    삼성웰스토리    2850    지출 NaN    2850  KRW   \n",
       "144 2018-01-04  [KB]      식비     식사      주신일과    1700    지출 NaN    1700  KRW   \n",
       "145 2018-01-03  [KB]      식비     식사    페퍼스레스토    5500    지출 NaN    5500  KRW   \n",
       "146 2018-01-03  [KB]      식비     커피    카이스트망고    2000    지출 NaN    2000  KRW   \n",
       "147 2018-01-03  [KB]      식비     식사    삼성웰스토리    2650    지출 NaN    2650  KRW   \n",
       "148 2018-01-03  [KB]      식비     식사      주신일과    1800    지출 NaN    1800  KRW   \n",
       "149 2018-01-02  [KB]      식비     야식      강변마트    1000    지출 NaN    1000  KRW   \n",
       "150 2018-01-02  [KB]      식비     식사    삼성웰스토리    3650    지출 NaN    3650  KRW   \n",
       "151 2018-01-02  [KB]      식비     간식       도너츠    1170    지출 NaN    1170  KRW   \n",
       "152 2018-01-02  [KB]      식비     식사    삼성웰스토리    2350    지출 NaN    2350  KRW   \n",
       "153 2018-01-01  [KB]      식비     야식    교촌치킨만년   15000    지출 NaN   15000  KRW   \n",
       "154 2018-01-01  [KB]      식비     간식     코레일유통    1500    지출 NaN    1500  KRW   \n",
       "155 2018-01-01  [KB]      식비     커피    엔제리너스서    4600    지출 NaN    4600  KRW   \n",
       "156 2018-01-01  [KB]      식비     커피      샵52랩    3000    지출 NaN    3000  KRW   \n",
       "157 2018-01-01  [KB]    생활용품   잡화소모    노트, 양말   17520    지출 NaN   17520  KRW   \n",
       "\n",
       "       자산.1  \n",
       "0      2300  \n",
       "1      4500  \n",
       "2      2000  \n",
       "3      3500  \n",
       "4       700  \n",
       "5      1872  \n",
       "6      3650  \n",
       "7      2000  \n",
       "8      3550  \n",
       "9      4100  \n",
       "10      700  \n",
       "11     3680  \n",
       "12     3666  \n",
       "13     1300  \n",
       "14     4000  \n",
       "15     2500  \n",
       "16     4000  \n",
       "17      700  \n",
       "18     4250  \n",
       "19   312760  \n",
       "20     3500  \n",
       "21    10400  \n",
       "22     2028  \n",
       "23     2500  \n",
       "24     7000  \n",
       "25     4000  \n",
       "26    20600  \n",
       "27     2000  \n",
       "28     3650  \n",
       "29    16000  \n",
       "..      ...  \n",
       "128    2500  \n",
       "129    3650  \n",
       "130    5200  \n",
       "131    2800  \n",
       "132   13000  \n",
       "133    2500  \n",
       "134    3650  \n",
       "135    2100  \n",
       "136   83480  \n",
       "137     700  \n",
       "138    7670  \n",
       "139   82180  \n",
       "140   20000  \n",
       "141    5000  \n",
       "142    4320  \n",
       "143    2850  \n",
       "144    1700  \n",
       "145    5500  \n",
       "146    2000  \n",
       "147    2650  \n",
       "148    1800  \n",
       "149    1000  \n",
       "150    3650  \n",
       "151    1170  \n",
       "152    2350  \n",
       "153   15000  \n",
       "154    1500  \n",
       "155    4600  \n",
       "156    3000  \n",
       "157   17520  \n",
       "\n",
       "[158 rows x 11 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receipt_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#  describe\n",
    "\n",
    "# 금액에 대한 histogram - python histogram plot \n",
    "\n",
    "# pandas groupby - 분류, 날짜 .sum() - pandas groupby\n",
    "\n",
    "# 야식 먹은 금액\n",
    "\n",
    "# 커피 금액 - 500 캡슐로 먹었다면 얼마나 차이가 나는가?\n",
    "\n",
    "# 식사를 어디서 얼만큼 식사를 했는가???"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>KRW</th>\n",
       "      <th>메모</th>\n",
       "      <th>금액</th>\n",
       "      <th>자산.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>158.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>158.000000</td>\n",
       "      <td>158.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9266.018987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9266.018987</td>\n",
       "      <td>9266.018987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>28692.921388</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28692.921388</td>\n",
       "      <td>28692.921388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>600.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600.000000</td>\n",
       "      <td>600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2033.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2033.500000</td>\n",
       "      <td>2033.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3500.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3500.000000</td>\n",
       "      <td>3500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4302.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4302.500000</td>\n",
       "      <td>4302.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>312760.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>312760.000000</td>\n",
       "      <td>312760.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 KRW   메모             금액           자산.1\n",
       "count     158.000000  0.0     158.000000     158.000000\n",
       "mean     9266.018987  NaN    9266.018987    9266.018987\n",
       "std     28692.921388  NaN   28692.921388   28692.921388\n",
       "min       600.000000  NaN     600.000000     600.000000\n",
       "25%      2033.500000  NaN    2033.500000    2033.500000\n",
       "50%      3500.000000  NaN    3500.000000    3500.000000\n",
       "75%      4302.500000  NaN    4302.500000    4302.500000\n",
       "max    312760.000000  NaN  312760.000000  312760.000000"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  describe\n",
    "receipt_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x8e622d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 금액에 대한 histogram - python histogram plot \n",
    "import matplotlib.pyplot as plt\n",
    "plt.title(\"KRW 히스토그램\")\n",
    "plt.hist(receipt_data[\"KRW\"], bins=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>KRW</th>\n",
       "      <th>메모</th>\n",
       "      <th>금액</th>\n",
       "      <th>자산.1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>분류</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>건강</th>\n",
       "      <td>16000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16000</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>경조사/회비</th>\n",
       "      <td>4100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4100</td>\n",
       "      <td>4100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>교통/차량</th>\n",
       "      <td>5445</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5445</td>\n",
       "      <td>5445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>기타</th>\n",
       "      <td>600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600</td>\n",
       "      <td>600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>생활용품</th>\n",
       "      <td>137640</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137640</td>\n",
       "      <td>137640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>식비</th>\n",
       "      <td>619336</td>\n",
       "      <td>NaN</td>\n",
       "      <td>619336</td>\n",
       "      <td>619336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>주거/통신</th>\n",
       "      <td>304160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>304160</td>\n",
       "      <td>304160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>패션/미용</th>\n",
       "      <td>376750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>376750</td>\n",
       "      <td>376750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           KRW  메모      금액    자산.1\n",
       "분류                                \n",
       "건강       16000 NaN   16000   16000\n",
       "경조사/회비    4100 NaN    4100    4100\n",
       "교통/차량     5445 NaN    5445    5445\n",
       "기타         600 NaN     600     600\n",
       "생활용품    137640 NaN  137640  137640\n",
       "식비      619336 NaN  619336  619336\n",
       "주거/통신   304160 NaN  304160  304160\n",
       "패션/미용   376750 NaN  376750  376750"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receipt_data.groupby(\"분류\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>KRW</th>\n",
       "      <th>메모</th>\n",
       "      <th>금액</th>\n",
       "      <th>자산.1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>날짜</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>41620</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41620</td>\n",
       "      <td>41620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>8170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8170</td>\n",
       "      <td>8170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>11950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11950</td>\n",
       "      <td>11950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>123720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>123720</td>\n",
       "      <td>123720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>86280</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86280</td>\n",
       "      <td>86280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-06</th>\n",
       "      <td>27150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27150</td>\n",
       "      <td>27150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-07</th>\n",
       "      <td>12022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12022</td>\n",
       "      <td>12022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>132410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>132410</td>\n",
       "      <td>132410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-09</th>\n",
       "      <td>20700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20700</td>\n",
       "      <td>20700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-10</th>\n",
       "      <td>12950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12950</td>\n",
       "      <td>12950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-11</th>\n",
       "      <td>22322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22322</td>\n",
       "      <td>22322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-12</th>\n",
       "      <td>16730</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16730</td>\n",
       "      <td>16730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-13</th>\n",
       "      <td>37050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37050</td>\n",
       "      <td>37050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-14</th>\n",
       "      <td>62028</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62028</td>\n",
       "      <td>62028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-15</th>\n",
       "      <td>62490</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62490</td>\n",
       "      <td>62490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-16</th>\n",
       "      <td>12332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12332</td>\n",
       "      <td>12332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-17</th>\n",
       "      <td>11000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11000</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-18</th>\n",
       "      <td>14075</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14075</td>\n",
       "      <td>14075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-19</th>\n",
       "      <td>25150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25150</td>\n",
       "      <td>25150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-20</th>\n",
       "      <td>31590</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31590</td>\n",
       "      <td>31590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-21</th>\n",
       "      <td>17436</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17436</td>\n",
       "      <td>17436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <td>106200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106200</td>\n",
       "      <td>106200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-23</th>\n",
       "      <td>28096</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28096</td>\n",
       "      <td>28096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-24</th>\n",
       "      <td>13250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13250</td>\n",
       "      <td>13250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-25</th>\n",
       "      <td>80204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80204</td>\n",
       "      <td>80204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-26</th>\n",
       "      <td>25700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25700</td>\n",
       "      <td>25700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-27</th>\n",
       "      <td>30250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30250</td>\n",
       "      <td>30250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-28</th>\n",
       "      <td>342438</td>\n",
       "      <td>NaN</td>\n",
       "      <td>342438</td>\n",
       "      <td>342438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-29</th>\n",
       "      <td>19846</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19846</td>\n",
       "      <td>19846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-30</th>\n",
       "      <td>15872</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15872</td>\n",
       "      <td>15872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-31</th>\n",
       "      <td>13000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13000</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               KRW  메모      금액    자산.1\n",
       "날짜                                    \n",
       "2018-01-01   41620 NaN   41620   41620\n",
       "2018-01-02    8170 NaN    8170    8170\n",
       "2018-01-03   11950 NaN   11950   11950\n",
       "2018-01-04  123720 NaN  123720  123720\n",
       "2018-01-05   86280 NaN   86280   86280\n",
       "2018-01-06   27150 NaN   27150   27150\n",
       "2018-01-07   12022 NaN   12022   12022\n",
       "2018-01-08  132410 NaN  132410  132410\n",
       "2018-01-09   20700 NaN   20700   20700\n",
       "2018-01-10   12950 NaN   12950   12950\n",
       "2018-01-11   22322 NaN   22322   22322\n",
       "2018-01-12   16730 NaN   16730   16730\n",
       "2018-01-13   37050 NaN   37050   37050\n",
       "2018-01-14   62028 NaN   62028   62028\n",
       "2018-01-15   62490 NaN   62490   62490\n",
       "2018-01-16   12332 NaN   12332   12332\n",
       "2018-01-17   11000 NaN   11000   11000\n",
       "2018-01-18   14075 NaN   14075   14075\n",
       "2018-01-19   25150 NaN   25150   25150\n",
       "2018-01-20   31590 NaN   31590   31590\n",
       "2018-01-21   17436 NaN   17436   17436\n",
       "2018-01-22  106200 NaN  106200  106200\n",
       "2018-01-23   28096 NaN   28096   28096\n",
       "2018-01-24   13250 NaN   13250   13250\n",
       "2018-01-25   80204 NaN   80204   80204\n",
       "2018-01-26   25700 NaN   25700   25700\n",
       "2018-01-27   30250 NaN   30250   30250\n",
       "2018-01-28  342438 NaN  342438  342438\n",
       "2018-01-29   19846 NaN   19846   19846\n",
       "2018-01-30   15872 NaN   15872   15872\n",
       "2018-01-31   13000 NaN   13000   13000"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receipt_data.groupby(\"날짜\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "161700"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receipt_data[receipt_data[\"소분류\"] == \"야식\"][\"KRW\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "66952\n"
     ]
    }
   ],
   "source": [
    "total_coffee_price = receipt_data[receipt_data[\"소분류\"] == \"커피\"][\"KRW\"].sum()\n",
    "capsule_coffee_price = len(receipt_data[receipt_data[\"소분류\"] == \"커피\"]) *  500\n",
    "print(total_coffee_price - capsule_coffee_price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "삼성웰스토리      26\n",
       "(주)신세계       7\n",
       "주신일과         7\n",
       "주식회사아이       6\n",
       "써브웨이대전       4\n",
       "NICE_배달의     3\n",
       "던킨도너츠대       3\n",
       "주식회사엠제       2\n",
       "1117meal     1\n",
       "새벽회          1\n",
       "지코바치킨        1\n",
       "만개           1\n",
       "페퍼스레스토       1\n",
       "고봉민김밥인       1\n",
       "모리모리         1\n",
       "한우국밥         1\n",
       "Name: 내용, dtype: int64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receipt_data[receipt_data[\"소분류\"]==\"식사\"][\"내용\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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