Code/3-pandas玩转数据/4-DataFrame的merge操作.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# DataFrame的merge操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame({'Key': ['X', 'Y', 'Z'], 'data_set_1': [1, 2, 3]})\n",
    "df2 = pd.DataFrame({'Key': ['X', 'B', 'C'], 'data_set_2': [4, 5, 6]})"
   ]
  },
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   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Key</th>\n",
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       "      <th>data_set_2</th>\n",
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
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      "text/plain": [
       "  Key  data_set_1  data_set_2\n",
       "0   X           1           4\n",
       "1   X           2           4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 合并（类似于 SQL中的 join 操作）参考：https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html\n",
    "pd.merge(df1, df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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