Solution/Day_09_Solution_v2.ipynb

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    "# [作業目標]\n",
    "\n",
    "1. 請建立類似提供結果的 DataFrame：\n",
    "\n",
    "```\n",
    "#    Apples  Bananas\n",
    "# 0      30       21\n",
    "\n",
    "#             Apples  Bananas\n",
    "# 2017 Sales      35       21\n",
    "# 2018 Sales      41       34\n",
    "\n",
    "```\n",
    "\n",
    "2. 請問如果現在有一個 DataFrame 如下，請問資料在 Python 中可能長怎樣？\n",
    "\n",
    "```\n",
    "#      city  visitor weekday\n",
    "# 0  Austin      139     Sun\n",
    "# 1  Dallas      237     Sun\n",
    "# 2  Austin      326     Mon\n",
    "# 3  Dallas      456     Mon\n",
    "```\n",
    "\n",
    "3. 假設你想知道每個 weekday 的平均 visitor 數量，可以怎麼做？\n"
   ]
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   "source": [
    "# 作業 "
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 請建立類似提供結果的 DataFrame：\n",
    "\n",
    "```\n",
    "#    Apples  Bananas\n",
    "# 0      30       21\n",
    "\n",
    "#             Apples  Bananas\n",
    "# 2017 Sales      35       21\n",
    "# 2018 Sales      41       34\n",
    "\n",
    "```\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 記得先 Import 正確的套件\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
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     "text": [
      "   Apples  Bananas\n",
      "0      30       21\n",
      "            Apples  Bananas\n",
      "2017 Sales      30       21\n",
      "2018 Sales      41       34\n"
     ]
    }
   ],
   "source": [
    "# 參考解答：方法一（from lict）\n",
    "\n",
    "# 1. Create a DataFrame `fruits` that looks like left:\n",
    "\n",
    "df = pd.DataFrame([[30, 21]], columns=['Apples', 'Bananas'])\n",
    "print(df)\n",
    "\n",
    "\n",
    "# 2. Create a dataframe `fruit_sales` that matches the diagram right:\n",
    "\n",
    "df = pd.DataFrame([[30, 21], [41, 34]], columns=['Apples', 'Bananas'], index=['2017 Sales', '2018 Sales'])\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 請問如果現在有一個 DataFrame 如下，請問資料在 Python 中可能長怎樣？\n",
    "\n",
    "```\n",
    "#      city  visitor weekday\n",
    "# 0  Austin      139     Sun\n",
    "# 1  Dallas      237     Sun\n",
    "# 2  Austin      326     Mon\n",
    "# 3  Dallas      456     Mon\n",
    "```\n",
    "\n"
   ]
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     "text": [
      "     city  visitor weekday\n",
      "0  Austin      139     Sun\n",
      "1  Dallas      237     Sun\n",
      "2  Austin      139     Mon\n",
      "3  Dallas      456     Mon\n"
     ]
    },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "      <th>visitor</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>Austin</td>\n",
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       "      <td>Mon</td>\n",
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       "      <td>Dallas</td>\n",
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       "      <td>Mon</td>\n",
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       "     city  visitor weekday\n",
       "0  Austin      139     Sun\n",
       "1  Dallas      237     Sun\n",
       "2  Austin      139     Mon\n",
       "3  Dallas      456     Mon"
      ]
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    "# 參考解答：方法二\n",
    "\n",
    "d = [\n",
    "    ['Austin', 139, 'Sun'],\n",
    "    ['Dallas', 237, 'Sun'],\n",
    "    ['Austin', 139, 'Mon'],\n",
    "    ['Dallas', 456, 'Mon'],\n",
    "]\n",
    "\n",
    "df = pd.DataFrame(d, columns=['city', 'visitor', 'weekday'])\n",
    "print(df)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. 承上題，假設你想知道每個 weekday 的平均 visitor 數量，可以怎麼做？\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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     "text": [
      "Sun 188.0\n",
      "Mon 297.5\n"
     ]
    }
   ],
   "source": [
    "# 參考解答\n",
    "for day in set(df['weekday']):\n",
    "    print(day, df[df['weekday'] == day]['visitor'].mean())"
   ]
  },
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   "execution_count": null,
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