Day_019_HW-EDA_subplots.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 作業\n",
    "### 請使用 application_train.csv, 根據不同的 HOUSETYPE_MODE 對 AMT_CREDIT 繪製 Histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [作業目標]\n",
    "- 試著調整資料, 並利用提供的程式繪製分布圖"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [作業重點]\n",
    "- 如何將列出相異的 HOUSETYPE_MODE 類別 (In[3])\n",
    "- 如何依照不同的 HOUSETYPE_MODE 類別指定資料, 並繪製長條圖(.hist())? (In[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 載入需要的套件\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns # 另一個繪圖-樣式套件\n",
    "\n",
    "# 忽略警告訊息\n",
    "%matplotlib inline\n",
    "plt.style.use('ggplot')\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# 設定 data_path\n",
    "# dir_data = './data/'\n",
    "# f_app = os.path.join(dir_data, 'application_train.csv')\n",
    "# print('Path of read in data: %s' % (f_app))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SK_ID_CURR</th>\n",
       "      <th>TARGET</th>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>AMT_CREDIT</th>\n",
       "      <th>AMT_ANNUITY</th>\n",
       "      <th>...</th>\n",
       "      <th>FLAG_DOCUMENT_18</th>\n",
       "      <th>FLAG_DOCUMENT_19</th>\n",
       "      <th>FLAG_DOCUMENT_20</th>\n",
       "      <th>FLAG_DOCUMENT_21</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_HOUR</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_DAY</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_WEEK</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_MON</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_QRT</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100002</td>\n",
       "      <td>1</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>202500.0</td>\n",
       "      <td>406597.5</td>\n",
       "      <td>24700.5</td>\n",
       "      <td>...</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100003</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>1293502.5</td>\n",
       "      <td>35698.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100004</td>\n",
       "      <td>0</td>\n",
       "      <td>Revolving loans</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>67500.0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>6750.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100006</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>312682.5</td>\n",
       "      <td>29686.5</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>100007</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>121500.0</td>\n",
       "      <td>513000.0</td>\n",
       "      <td>21865.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 122 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
       "0      100002       1         Cash loans           M            N   \n",
       "1      100003       0         Cash loans           F            N   \n",
       "2      100004       0    Revolving loans           M            Y   \n",
       "3      100006       0         Cash loans           F            N   \n",
       "4      100007       0         Cash loans           M            N   \n",
       "\n",
       "  FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  AMT_ANNUITY  \\\n",
       "0               Y             0          202500.0    406597.5      24700.5   \n",
       "1               N             0          270000.0   1293502.5      35698.5   \n",
       "2               Y             0           67500.0    135000.0       6750.0   \n",
       "3               Y             0          135000.0    312682.5      29686.5   \n",
       "4               Y             0          121500.0    513000.0      21865.5   \n",
       "\n",
       "   ...  FLAG_DOCUMENT_18 FLAG_DOCUMENT_19 FLAG_DOCUMENT_20 FLAG_DOCUMENT_21  \\\n",
       "0  ...                 0                0                0                0   \n",
       "1  ...                 0                0                0                0   \n",
       "2  ...                 0                0                0                0   \n",
       "3  ...                 0                0                0                0   \n",
       "4  ...                 0                0                0                0   \n",
       "\n",
       "  AMT_REQ_CREDIT_BUREAU_HOUR AMT_REQ_CREDIT_BUREAU_DAY  \\\n",
       "0                        0.0                       0.0   \n",
       "1                        0.0                       0.0   \n",
       "2                        0.0                       0.0   \n",
       "3                        NaN                       NaN   \n",
       "4                        0.0                       0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_WEEK  AMT_REQ_CREDIT_BUREAU_MON  \\\n",
       "0                         0.0                        0.0   \n",
       "1                         0.0                        0.0   \n",
       "2                         0.0                        0.0   \n",
       "3                         NaN                        NaN   \n",
       "4                         0.0                        0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_QRT  AMT_REQ_CREDIT_BUREAU_YEAR  \n",
       "0                        0.0                         1.0  \n",
       "1                        0.0                         0.0  \n",
       "2                        0.0                         0.0  \n",
       "3                        NaN                         NaN  \n",
       "4                        0.0                         0.0  \n",
       "\n",
       "[5 rows x 122 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 讀取檔案\n",
    "app_train = pd.read_csv(r\"C:\\Users\\user\\100 days\\data\\application_train.csv\")\n",
    "app_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>SK_ID_CURR</th>\n",
       "      <th>TARGET</th>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
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       "      <th>AMT_CREDIT</th>\n",
       "      <th>AMT_ANNUITY</th>\n",
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       "      <th>FLAG_DOCUMENT_19</th>\n",
       "      <th>FLAG_DOCUMENT_20</th>\n",
       "      <th>FLAG_DOCUMENT_21</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_HOUR</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_DAY</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_WEEK</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_MON</th>\n",
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       "      <td>N</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100004</td>\n",
       "      <td>0</td>\n",
       "      <td>Revolving loans</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>67500.0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>6750.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100006</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>135000.0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>100007</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>121500.0</td>\n",
       "      <td>513000.0</td>\n",
       "      <td>21865.5</td>\n",
       "      <td>...</td>\n",
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      ],
      "text/plain": [
       "   SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
       "0      100002       1         Cash loans           M            N   \n",
       "1      100003       0         Cash loans           F            N   \n",
       "2      100004       0    Revolving loans           M            Y   \n",
       "3      100006       0         Cash loans           F            N   \n",
       "4      100007       0         Cash loans           M            N   \n",
       "\n",
       "  FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  AMT_ANNUITY  \\\n",
       "0               Y             0          202500.0    406597.5      24700.5   \n",
       "1               N             0          270000.0   1293502.5      35698.5   \n",
       "2               Y             0           67500.0    135000.0       6750.0   \n",
       "3               Y             0          135000.0    312682.5      29686.5   \n",
       "4               Y             0          121500.0    513000.0      21865.5   \n",
       "\n",
       "   ...  FLAG_DOCUMENT_18 FLAG_DOCUMENT_19 FLAG_DOCUMENT_20 FLAG_DOCUMENT_21  \\\n",
       "0  ...                 0                0                0                0   \n",
       "1  ...                 0                0                0                0   \n",
       "2  ...                 0                0                0                0   \n",
       "3  ...                 0                0                0                0   \n",
       "4  ...                 0                0                0                0   \n",
       "\n",
       "  AMT_REQ_CREDIT_BUREAU_HOUR AMT_REQ_CREDIT_BUREAU_DAY  \\\n",
       "0                        0.0                       0.0   \n",
       "1                        0.0                       0.0   \n",
       "2                        0.0                       0.0   \n",
       "3                        NaN                       NaN   \n",
       "4                        0.0                       0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_WEEK  AMT_REQ_CREDIT_BUREAU_MON  \\\n",
       "0                         0.0                        0.0   \n",
       "1                         0.0                        0.0   \n",
       "2                         0.0                        0.0   \n",
       "3                         NaN                        NaN   \n",
       "4                         0.0                        0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_QRT  AMT_REQ_CREDIT_BUREAU_YEAR  \n",
       "0                        0.0                         1.0  \n",
       "1                        0.0                         0.0  \n",
       "2                        0.0                         0.0  \n",
       "3                        NaN                         NaN  \n",
       "4                        0.0                         0.0  \n",
       "\n",
       "[5 rows x 122 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 資料分群後排序\n",
    "unique_house_type = app_train['HOUSETYPE_MODE'].unique()\n",
    "app_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         block of flats\n",
       "1         block of flats\n",
       "2                    NaN\n",
       "3                    NaN\n",
       "4                    NaN\n",
       "5                    NaN\n",
       "6                    NaN\n",
       "7                    NaN\n",
       "8                    NaN\n",
       "9                    NaN\n",
       "10                   NaN\n",
       "11                   NaN\n",
       "12        block of flats\n",
       "13        block of flats\n",
       "14        block of flats\n",
       "15                   NaN\n",
       "16                   NaN\n",
       "17                   NaN\n",
       "18        block of flats\n",
       "19                   NaN\n",
       "20        block of flats\n",
       "21                   NaN\n",
       "22        block of flats\n",
       "23        block of flats\n",
       "24        block of flats\n",
       "25        block of flats\n",
       "26        block of flats\n",
       "27                   NaN\n",
       "28                   NaN\n",
       "29        block of flats\n",
       "               ...      \n",
       "307481               NaN\n",
       "307482    block of flats\n",
       "307483    block of flats\n",
       "307484               NaN\n",
       "307485               NaN\n",
       "307486    block of flats\n",
       "307487               NaN\n",
       "307488               NaN\n",
       "307489    block of flats\n",
       "307490               NaN\n",
       "307491               NaN\n",
       "307492               NaN\n",
       "307493               NaN\n",
       "307494               NaN\n",
       "307495    block of flats\n",
       "307496               NaN\n",
       "307497               NaN\n",
       "307498    block of flats\n",
       "307499               NaN\n",
       "307500    block of flats\n",
       "307501    block of flats\n",
       "307502               NaN\n",
       "307503               NaN\n",
       "307504               NaN\n",
       "307505    block of flats\n",
       "307506    block of flats\n",
       "307507    block of flats\n",
       "307508    block of flats\n",
       "307509    block of flats\n",
       "307510    block of flats\n",
       "Name: HOUSETYPE_MODE, Length: 307511, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "app_train['HOUSETYPE_MODE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2160 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 使用不同的 HOUSETYPE_MODE 類別繪製圖形, 並使用 subplot 排版\n",
    "\n",
    "nrows = len(unique_house_type)\n",
    "ncols = nrows // 2\n",
    "\n",
    "plt.figure(figsize=(10,30))\n",
    "for i in range(len(unique_house_type)):\n",
    "    plt.subplot(nrows, ncols, i+1)\n",
    "    sns.distplot(app_train.loc[(app_train['HOUSETYPE_MODE'] == unique_house_type[i]) & (app_train['TARGET'] == 0), 'AMT_CREDIT'], \n",
    "                 label = \"TARGET = 0\", hist = True)\n",
    "    plt.title(str(unique_house_type[i]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2160 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 使用不同的 HOUSETYPE_MODE 類別繪製圖形, 並使用 subplot 排版\n",
    "\"\"\"\n",
    "Your Code Here\n",
    "\"\"\"\n",
    "unique_house_type = app_train['HOUSETYPE_MODE'].unique()\n",
    "\n",
    "nrows = len(unique_house_type)\n",
    "ncols = nrows // 2\n",
    "\n",
    "plt.figure(figsize=(10,30))\n",
    "for i in range(len(unique_house_type)):\n",
    "    plt.subplot(nrows, ncols, i+1)\n",
    "    \"\"\"\n",
    "    Your Code Here\n",
    "    \"\"\"\n",
    "    app_train.loc[app_train['HOUSETYPE_MODE'] == unique_house_type[i], \"AMT_CREDIT\"].hist()\n",
    "    plt.title(str(unique_house_type[i]))\n",
    "plt.show()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2019/09/22 待更新\n",
    "# app_train.loc[,].hist() ...怎用?  畫出來不一樣..."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}