pies.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "f25563ab-b701-4492-88d8-3edac9149852",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df1 = pd.read_csv(r\".\\卫星测高.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d0d2b3ae-8600-4a47-afe6-0102514bbaab",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>项目标题</th>\n",
       "      <th>所属学部</th>\n",
       "      <th>项目类型</th>\n",
       "      <th>项目编号</th>\n",
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       "      <th>负责人</th>\n",
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       "      <th>二级学科</th>\n",
       "      <th>二级代码</th>\n",
       "      <th>三级学科</th>\n",
       "      <th>三级代码</th>\n",
       "      <th>执行起自</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>基于宽刈幅测高资料的东海黑潮两侧亚中尺度过程三维结构特征分析</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>42106031.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>庄展鹏</td>\n",
       "      <td>自然资源部第一海洋研究所</td>\n",
       "      <td>2021.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>基于星载激光测高仪多模式回波的地形参数反演研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41971302.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>周辉</td>\n",
       "      <td>武汉大学</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>地理学</td>\n",
       "      <td>D01</td>\n",
       "      <td>遥感机理与方法</td>\n",
       "      <td>D0106</td>\n",
       "      <td>遥感机理与方法</td>\n",
       "      <td>D0106</td>\n",
       "      <td>2020-01</td>\n",
       "      <td>2023-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>基于GNSS、长期验潮站与卫星测高联合观测的中国沿海绝对海平面变化研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>41706115.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>周东旭</td>\n",
       "      <td>自然资源部第一海洋研究所</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>海洋科学</td>\n",
       "      <td>D06</td>\n",
       "      <td>海洋物理与观测探测技术</td>\n",
       "      <td>D0608</td>\n",
       "      <td>海洋物理与观测探测技术</td>\n",
       "      <td>D0608</td>\n",
       "      <td>2018-01</td>\n",
       "      <td>2020-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>面向高分辨率、宽刈幅海面测高资料的高效同化方法</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>42006008.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>周超杰</td>\n",
       "      <td>中国石油大学（华东）</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>海洋科学</td>\n",
       "      <td>D06</td>\n",
       "      <td>物理海洋学</td>\n",
       "      <td>D0601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>联合航空矢量重力测量和卫星测高精化海岸带大地水准面</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>41504013.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>周波阳</td>\n",
       "      <td>广东工业大学</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>大地测量学</td>\n",
       "      <td>D0401</td>\n",
       "      <td>物理大地测量学</td>\n",
       "      <td>D040101</td>\n",
       "      <td>2016-01</td>\n",
       "      <td>2018-12</td>\n",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>70</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   项目标题   所属学部      项目类型        项目编号  金额（万）  \\\n",
       "0        基于宽刈幅测高资料的东海黑潮两侧亚中尺度过程三维结构特征分析  地球科学部  青年科学基金项目  42106031.0   30.0   \n",
       "1               基于星载激光测高仪多模式回波的地形参数反演研究  地球科学部      面上项目  41971302.0   53.0   \n",
       "2   基于GNSS、长期验潮站与卫星测高联合观测的中国沿海绝对海平面变化研究  地球科学部  青年科学基金项目  41706115.0   25.0   \n",
       "3               面向高分辨率、宽刈幅海面测高资料的高效同化方法  地球科学部  青年科学基金项目  42006008.0   24.0   \n",
       "4             联合航空矢量重力测量和卫星测高精化海岸带大地水准面  地球科学部  青年科学基金项目  41504013.0   21.0   \n",
       "..                                  ...    ...       ...         ...    ...   \n",
       "67                                  NaN    NaN       NaN         NaN    NaN   \n",
       "68                                  NaN    NaN       NaN         NaN    NaN   \n",
       "69                                  NaN    NaN       NaN         NaN    NaN   \n",
       "70                                  NaN    NaN       NaN         NaN    NaN   \n",
       "71                                  NaN    NaN       NaN         NaN    NaN   \n",
       "\n",
       "    负责人            单位    批准年份         一级学科 一级代码         二级学科   二级代码  \\\n",
       "0   庄展鹏  自然资源部第一海洋研究所  2021.0          NaN  NaN          NaN    NaN   \n",
       "1    周辉          武汉大学  2019.0          地理学  D01      遥感机理与方法  D0106   \n",
       "2   周东旭  自然资源部第一海洋研究所  2017.0         海洋科学  D06  海洋物理与观测探测技术  D0608   \n",
       "3   周超杰    中国石油大学（华东）  2020.0         海洋科学  D06        物理海洋学  D0601   \n",
       "4   周波阳        广东工业大学  2015.0  地球物理学和空间物理学  D04        大地测量学  D0401   \n",
       "..  ...           ...     ...          ...  ...          ...    ...   \n",
       "67  NaN           NaN     NaN          NaN  NaN          NaN    NaN   \n",
       "68  NaN           NaN     NaN          NaN  NaN          NaN    NaN   \n",
       "69  NaN           NaN     NaN          NaN  NaN          NaN    NaN   \n",
       "70  NaN           NaN     NaN          NaN  NaN          NaN    NaN   \n",
       "71  NaN           NaN     NaN          NaN  NaN          NaN    NaN   \n",
       "\n",
       "           三级学科     三级代码     执行起自     执行截至  \n",
       "0           NaN      NaN    FALSE    FALSE  \n",
       "1       遥感机理与方法    D0106  2020-01  2023-12  \n",
       "2   海洋物理与观测探测技术    D0608  2018-01  2020-12  \n",
       "3           NaN      NaN    FALSE    FALSE  \n",
       "4       物理大地测量学  D040101  2016-01  2018-12  \n",
       "..          ...      ...      ...      ...  \n",
       "67          NaN      NaN      NaN      NaN  \n",
       "68          NaN      NaN      NaN      NaN  \n",
       "69          NaN      NaN      NaN      NaN  \n",
       "70          NaN      NaN      NaN      NaN  \n",
       "71          NaN      NaN      NaN      NaN  \n",
       "\n",
       "[72 rows x 16 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "23914290-da30-4a19-9cbb-ab1f56541f5a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 72 entries, 0 to 71\n",
      "Data columns (total 16 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   项目标题    66 non-null     object \n",
      " 1   所属学部    66 non-null     object \n",
      " 2   项目类型    66 non-null     object \n",
      " 3   项目编号    61 non-null     float64\n",
      " 4   金额（万）   66 non-null     float64\n",
      " 5   负责人     66 non-null     object \n",
      " 6   单位      66 non-null     object \n",
      " 7   批准年份    66 non-null     float64\n",
      " 8   一级学科    55 non-null     object \n",
      " 9   一级代码    55 non-null     object \n",
      " 10  二级学科    55 non-null     object \n",
      " 11  二级代码    55 non-null     object \n",
      " 12  三级学科    34 non-null     object \n",
      " 13  三级代码    34 non-null     object \n",
      " 14  执行起自    64 non-null     object \n",
      " 15  执行截至    64 non-null     object \n",
      "dtypes: float64(3), object(13)\n",
      "memory usage: 9.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "ec4f7593-6b48-4622-a60a-890fd05a9a21",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=df1.head(66)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c92b9091-c406-4eb9-bdaf-8124c9812bed",
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   "outputs": [
    {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>基于宽刈幅测高资料的东海黑潮两侧亚中尺度过程三维结构特征分析</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>42106031.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>庄展鹏</td>\n",
       "      <td>自然资源部第一海洋研究所</td>\n",
       "      <td>2021.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>基于星载激光测高仪多模式回波的地形参数反演研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41971302.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>周辉</td>\n",
       "      <td>武汉大学</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>地理学</td>\n",
       "      <td>D01</td>\n",
       "      <td>遥感机理与方法</td>\n",
       "      <td>D0106</td>\n",
       "      <td>遥感机理与方法</td>\n",
       "      <td>D0106</td>\n",
       "      <td>2020-01</td>\n",
       "      <td>2023-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>基于GNSS、长期验潮站与卫星测高联合观测的中国沿海绝对海平面变化研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>41706115.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>周东旭</td>\n",
       "      <td>自然资源部第一海洋研究所</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>海洋科学</td>\n",
       "      <td>D06</td>\n",
       "      <td>海洋物理与观测探测技术</td>\n",
       "      <td>D0608</td>\n",
       "      <td>海洋物理与观测探测技术</td>\n",
       "      <td>D0608</td>\n",
       "      <td>2018-01</td>\n",
       "      <td>2020-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>面向高分辨率、宽刈幅海面测高资料的高效同化方法</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>42006008.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>周超杰</td>\n",
       "      <td>中国石油大学（华东）</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>海洋科学</td>\n",
       "      <td>D06</td>\n",
       "      <td>物理海洋学</td>\n",
       "      <td>D0601</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>联合航空矢量重力测量和卫星测高精化海岸带大地水准面</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>41504013.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>周波阳</td>\n",
       "      <td>广东工业大学</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>大地测量学</td>\n",
       "      <td>D0401</td>\n",
       "      <td>物理大地测量学</td>\n",
       "      <td>D040101</td>\n",
       "      <td>2016-01</td>\n",
       "      <td>2018-12</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>合成孔径高度计回波波形的经验函数模型构建与抗差估计方法研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41674082.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>翟振和</td>\n",
       "      <td>西安测绘研究所</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>重力学</td>\n",
       "      <td>D0405</td>\n",
       "      <td>重力学</td>\n",
       "      <td>D0405</td>\n",
       "      <td>2017-01</td>\n",
       "      <td>2020-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>国产海洋动力卫星陆表水循环关键参数反演模型与不确定性研究</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41976171.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>陈权</td>\n",
       "      <td>中国科学院遥感与数字地球研究所</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>海洋科学</td>\n",
       "      <td>D06</td>\n",
       "      <td>海洋遥感</td>\n",
       "      <td>D0607</td>\n",
       "      <td>海洋遥感</td>\n",
       "      <td>D0607</td>\n",
       "      <td>2020-01</td>\n",
       "      <td>2023-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>融合多源卫星观测数据精确量化长江流域水资源时空演变特性</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41974019.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>超能芳</td>\n",
       "      <td>中国地质大学（武汉）</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>物理大地测量学</td>\n",
       "      <td>D0401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>联合多源数据研究长江源区冰川质量变化及其对水资源影响</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>青年科学基金项目</td>\n",
       "      <td>41704011.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>超能芳</td>\n",
       "      <td>华中科技大学</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>物理大地测量学</td>\n",
       "      <td>D0401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>标定雷达高度计资料测定内陆水变化理论方法及其在地下水监测中应用</td>\n",
       "      <td>地球科学部</td>\n",
       "      <td>面上项目</td>\n",
       "      <td>41574001.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>Vagner G.Ferreira</td>\n",
       "      <td>河海大学</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>地球物理学和空间物理学</td>\n",
       "      <td>D04</td>\n",
       "      <td>物理大地测量学</td>\n",
       "      <td>D0401</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>FALSE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   项目标题   所属学部      项目类型        项目编号  金额（万）  \\\n",
       "0        基于宽刈幅测高资料的东海黑潮两侧亚中尺度过程三维结构特征分析  地球科学部  青年科学基金项目  42106031.0   30.0   \n",
       "1               基于星载激光测高仪多模式回波的地形参数反演研究  地球科学部      面上项目  41971302.0   53.0   \n",
       "2   基于GNSS、长期验潮站与卫星测高联合观测的中国沿海绝对海平面变化研究  地球科学部  青年科学基金项目  41706115.0   25.0   \n",
       "3               面向高分辨率、宽刈幅海面测高资料的高效同化方法  地球科学部  青年科学基金项目  42006008.0   24.0   \n",
       "4             联合航空矢量重力测量和卫星测高精化海岸带大地水准面  地球科学部  青年科学基金项目  41504013.0   21.0   \n",
       "..                                  ...    ...       ...         ...    ...   \n",
       "61        合成孔径高度计回波波形的经验函数模型构建与抗差估计方法研究  地球科学部      面上项目  41674082.0   40.0   \n",
       "62         国产海洋动力卫星陆表水循环关键参数反演模型与不确定性研究  地球科学部      面上项目  41976171.0   62.0   \n",
       "63          融合多源卫星观测数据精确量化长江流域水资源时空演变特性  地球科学部      面上项目  41974019.0   63.0   \n",
       "64           联合多源数据研究长江源区冰川质量变化及其对水资源影响  地球科学部  青年科学基金项目  41704011.0   25.0   \n",
       "65      标定雷达高度计资料测定内陆水变化理论方法及其在地下水监测中应用  地球科学部      面上项目  41574001.0   70.0   \n",
       "\n",
       "                  负责人               单位    批准年份         一级学科 一级代码         二级学科  \\\n",
       "0                 庄展鹏     自然资源部第一海洋研究所  2021.0          NaN  NaN          NaN   \n",
       "1                  周辉             武汉大学  2019.0          地理学  D01      遥感机理与方法   \n",
       "2                 周东旭     自然资源部第一海洋研究所  2017.0         海洋科学  D06  海洋物理与观测探测技术   \n",
       "3                 周超杰       中国石油大学（华东）  2020.0         海洋科学  D06        物理海洋学   \n",
       "4                 周波阳           广东工业大学  2015.0  地球物理学和空间物理学  D04        大地测量学   \n",
       "..                ...              ...     ...          ...  ...          ...   \n",
       "61                翟振和          西安测绘研究所  2016.0  地球物理学和空间物理学  D04          重力学   \n",
       "62                 陈权  中国科学院遥感与数字地球研究所  2019.0         海洋科学  D06         海洋遥感   \n",
       "63                超能芳       中国地质大学（武汉）  2019.0  地球物理学和空间物理学  D04      物理大地测量学   \n",
       "64                超能芳           华中科技大学  2017.0  地球物理学和空间物理学  D04      物理大地测量学   \n",
       "65  Vagner G.Ferreira             河海大学  2015.0  地球物理学和空间物理学  D04      物理大地测量学   \n",
       "\n",
       "     二级代码         三级学科     三级代码     执行起自     执行截至  \n",
       "0     NaN          NaN      NaN    FALSE    FALSE  \n",
       "1   D0106      遥感机理与方法    D0106  2020-01  2023-12  \n",
       "2   D0608  海洋物理与观测探测技术    D0608  2018-01  2020-12  \n",
       "3   D0601          NaN      NaN    FALSE    FALSE  \n",
       "4   D0401      物理大地测量学  D040101  2016-01  2018-12  \n",
       "..    ...          ...      ...      ...      ...  \n",
       "61  D0405          重力学    D0405  2017-01  2020-12  \n",
       "62  D0607         海洋遥感    D0607  2020-01  2023-12  \n",
       "63  D0401          NaN      NaN    FALSE    FALSE  \n",
       "64  D0401          NaN      NaN    FALSE    FALSE  \n",
       "65  D0401          NaN      NaN    FALSE    FALSE  \n",
       "\n",
       "[66 rows x 16 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
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   "execution_count": 2,
   "id": "2c985509-3950-47d9-9db5-a5d59f6a69eb",
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   "source": [
    "# df1.loc[df1['Record Count'] < 200, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries\n",
    "# df2.loc[df2['Record Count'] < 200, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries\n",
    "# df3.loc[df3['Record Count'] < 200, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries\n",
    "# df4.loc[df4['Record Count'] < 200, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries\n",
    "# df5.loc[df5['Record Count'] < 50, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries\n",
    "# df6.loc[df6['Record Count'] < 50, 'Web of Science Categories'] = 'Other Categories' # Represent only large countries"
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "23d7d846-0aea-4183-bae8-492803b89a96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set Other Categories' value to 0.\n",
    "# df1.loc[df1['Record Count'] < 200, 'Record Count'] = '0' # Represent only large countries\n",
    "# df2.loc[df2['Record Count'] < 200, 'Record Count'] = '0' \n",
    "# df3.loc[df3['Record Count'] < 200, 'Record Count'] = '0' \n",
    "# df4.loc[df4['Record Count'] < 200, 'Record Count'] = '0' \n",
    "# df5.loc[df5['Record Count'] < 50, 'Record Count'] = '0' \n",
    "# df6.loc[df6['Record Count'] < 50, 'Record Count'] = '0' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "3824659a-068a-461d-8296-bde5df3b9a41",
   "metadata": {},
   "outputs": [
    {
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       "0     2021.0\n",
       "1     2019.0\n",
       "2     2017.0\n",
       "3     2020.0\n",
       "4     2015.0\n",
       "       ...  \n",
       "61    2016.0\n",
       "62    2019.0\n",
       "63    2019.0\n",
       "64    2017.0\n",
       "65    2015.0\n",
       "Name: 批准年份, Length: 66, dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "df1['批准年份']"
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  },
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   "execution_count": 59,
   "id": "8d3b5e8d-3b32-4361-b8ad-77130794c241",
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",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "fig = px.pie(df1,  names=df1['项目类型'],\n",
    "             # title='Population of American continent',\n",
    "            )\n",
    "\n",
    "fig.update_traces(textposition='inside',textinfo='label+value',showlegend=False,opacity=1,pull=0.00,hole=0.2)\n",
    "# fig.update_layout(uniformtext_minsize=9, uniformtext_mode='hide')\n",
    "\n",
    "fig.update_layout(\n",
    "    margin=dict(l=20, r=20, t=20, b=20),  # 上下左右的边距大小\n",
    "    paper_bgcolor=\"white\",  # 颜色\n",
    ")\n",
    "\n",
    "fig.update_layout(height=500,width=900)\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "id": "15a721ec-0734-41bd-a6da-8b3acb2a4b1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.write_image(\"fig-all.pdf\")"
   ]
  }
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