【数据分析与可视化】Pandas-Dataframe-IO操作

import numpy as np
import pandas as pd

import webbrowser

# 跳转页面
link = 'https://pandas.pydata.org/pandas-docs/version/1.0.2/user_guide/io.html'
webbrowser.open(link)

True

df1 = pd.read_clipboard()
df1

联系地址	所属部门	职位	职称	聘用形式	最高学历	专业	毕业院校
深圳市南山区	总办	技术总监	教授	劳务合同	本科	信息管理与信息系统	深圳大学
海南省海口市美兰区	技术部	技术总监	助教	劳动合同	高中	市场营销	武汉大学
陕西省西安市莲湖区	技术部	研发工程师	助教	劳动合同	博士	电子工程	哈尔滨理工大学
吉林通化	技术部	Java研发经理	高级工程师	劳动合同	本科	软件工程	西北师大

 df1.to_clipboard()

# 使用粘贴键（带序号，粘贴板，方便贴到excel上）
    联系地址	所属部门	职位	职称	聘用形式	最高学历	专业	毕业院校
0	深圳市南山区	总办	技术总监	教授	劳务合同	本科	信息管理与信息系统	深圳大学
1	海南省海口市美兰区	技术部	技术总监	助教	劳动合同	高中	市场营销	武汉大学
2	陕西省西安市莲湖区	技术部	研发工程师	助教	劳动合同	博士	电子工程	哈尔滨理工大学
3	吉林通化	技术部	Java研发经理	高级工程师	劳动合同	本科	软件工程	西北师大

# 保存到csv文件（通过参数index=False，控制存入是否带序号）
df1.to_csv('df1.csv',index=False)
# 查看文件是否存在
!ls

[35m2to3[m[m                                 [35mlzdiff[m[m
[31m2to3-3.7[m[m                             [35mlzegrep[m[m
3-4 Pandas-Dataframe-IO操作.ipynb    [35mlzfgrep[m[m
[34mAssistant.app[m[m                        [35mlzgrep[m[m
[34mDesigner.app[m[m                         [35mlzless[m[m
[34mLinguist.app[m[m                         [35mlzma[m[m
Numpy序列化.npy                      [31mlzmadec[m[m
Numpy多序列化.npz                    [31mlzmainfo[m[m
Pandas Dataframe.ipynb               [35mlzmore[m[m
Pandas Series.ipynb                  [31mmacchangeqt[m[m
Pandas数据载入与预处理.ipynb         [31mmacdeployqt[m[m
Python的input和output.ipynb          [31mmakeconv[m[m
[31mactivate[m[m                             [31mmoc[m[m
[31manaconda[m[m                             [31mmsgattrib[m[m
[31manaconda-navigator[m[m                   [31mmsgcat[m[m
[31manaconda-project[m[m                     [31mmsgcmp[m[m
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[31mbsdcat[m[m                               [31mmsgfilter[m[m
[31mbsdcpio[m[m                              [31mmsgfmt[m[m
[31mbsdtar[m[m                               [31mmsggrep[m[m
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df1.csv                              [35mpyvenv[m[m
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[31mjupyter-kernel[m[m                       [35munlzma[m[m
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[31mjupyter-serverextension[m[m              x.pkl
[31mjupyter-troubleshoot[m[m                 [34mxc-avoidance[m[m
[31mjupyter-trust[m[m                        [31mxgettext[m[m
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[31mk5srvutil[m[m                            [31mxml2-config[m[m
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[31mlconvert[m[m                             [35mxzegrep[m[m
[35mlibpng-config[m[m                        [35mxzfgrep[m[m
[31mlibpng16-config[m[m                      [31mxzgrep[m[m
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[31mlss3[m[m                                 [31mzstd[m[m
[31mlupdate[m[m                              [35mzstdcat[m[m
[31mlz4[m[m                                  [35mzstdmt[m[m
[35mlz4c[m[m                                 创建数组.ipynb
[35mlz4cat[m[m                               深入理解Series和DataFrame.ipynb
[35mlzcat[m[m                                作业与练习.ipynb
[35mlzcmp[m[m                                数组与矩阵运算.ipynb

# 查看csv文件内容（携带index）
!more df1.csv

联系地址,所属部门,职位,职称,聘用形式,最高学历,专业,毕业院校
深圳市南山区,总办,技术总监,教授,劳务合同,本科,信息管理与信息系统,深圳大学
海南省海口市美兰区,技术部,技术总监,助教,劳动合同,高中,市场营销,武汉大学
陕西省西安市莲湖区,技术部,研发工程师,助教,劳动合同,博士,电子工程,哈尔滨理工大学
吉林通化,技术部,Java研发经理,高级工程师,劳动合同,本科,软件工程,西北师大
[7mdf1.csv (END)[m[K

# 读取csv
df2 = pd.read_csv('df1.csv')
df2

# 转换成json（防中文乱码）
df2.to_json(force_ascii=False)

'{"联系地址":{"0":"深圳市南山区","1":"海南省海口市美兰区","2":"陕西省西安市莲湖区","3":"吉林通化"},"所属部门":{"0":"总办","1":"技术部","2":"技术部","3":"技术部"},"职位":{"0":"技术总监","1":"技术总监","2":"研发工程师","3":"Java研发经理"},"职称":{"0":"教授","1":"助教","2":"助教","3":"高级工程师"},"聘用形式":{"0":"劳务合同","1":"劳动合同","2":"劳动合同","3":"劳动合同"},"最高学历":{"0":"本科","1":"高中","2":"博士","3":"本科"},"专业":{"0":"信息管理与信息系统","1":"市场营销","2":"电子工程","3":"软件工程"},"毕业院校":{"0":"深圳大学","1":"武汉大学","2":"哈尔滨理工大学","3":"西北师大"}}'

# 读json成数据框
pd.read_json(df2.to_json())

# 转换成html （同上存储 读取）
df2.to_html()

'<table border="1" >\n  <thead>\n    <tr style="text-align: right;">\n      <th></th>\n      <th>联系地址</th>\n      <th>所属部门</th>\n      <th>职位</th>\n      <th>职称</th>\n      <th>聘用形式</th>\n      <th>最高学历</th>\n      <th>专业</th>\n      <th>毕业院校</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>深圳市南山区</td>\n      <td>总办</td>\n      <td>技术总监</td>\n      <td>教授</td>\n      <td>劳务合同</td>\n      <td>本科</td>\n      <td>信息管理与信息系统</td>\n      <td>深圳大学</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>海南省海口市美兰区</td>\n      <td>技术部</td>\n      <td>技术总监</td>\n      <td>助教</td>\n      <td>劳动合同</td>\n      <td>高中</td>\n      <td>市场营销</td>\n      <td>武汉大学</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>陕西省西安市莲湖区</td>\n      <td>技术部</td>\n      <td>研发工程师</td>\n      <td>助教</td>\n      <td>劳动合同</td>\n      <td>博士</td>\n      <td>电子工程</td>\n      <td>哈尔滨理工大学</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>吉林通化</td>\n      <td>技术部</td>\n      <td>Java研发经理</td>\n      <td>高级工程师</td>\n      <td>劳动合同</td>\n      <td>本科</td>\n      <td>软件工程</td>\n      <td>西北师大</td>\n    </tr>\n  </tbody>\n</table>'

df2.to_excel('df2.xlsx')
!ls

[35m2to3[m[m                                 [35mlzdiff[m[m
[31m2to3-3.7[m[m                             [35mlzegrep[m[m
3-4 Pandas-Dataframe-IO操作.ipynb    [35mlzfgrep[m[m
[34mAssistant.app[m[m                        [35mlzgrep[m[m
[34mDesigner.app[m[m                         [35mlzless[m[m
[34mLinguist.app[m[m                         [35mlzma[m[m
Numpy序列化.npy                      [31mlzmadec[m[m
Numpy多序列化.npz                    [31mlzmainfo[m[m
Pandas Dataframe.ipynb               [35mlzmore[m[m
Pandas Series.ipynb                  [31mmacchangeqt[m[m
Pandas数据载入与预处理.ipynb         [31mmacdeployqt[m[m
Python的input和output.ipynb          [31mmakeconv[m[m
[31mactivate[m[m                             [31mmoc[m[m
[31manaconda[m[m                             [31mmsgattrib[m[m
[31manaconda-navigator[m[m                   [31mmsgcat[m[m
[31manaconda-project[m[m                     [31mmsgcmp[m[m
[31masadmin[m[m                              [31mmsgcomm[m[m
[31mautopoint[m[m                            [31mmsgconv[m[m
[31mbinstar[m[m                              [31mmsgen[m[m
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[31mbsdcat[m[m                               [31mmsgfilter[m[m
[31mbsdcpio[m[m                              [31mmsgfmt[m[m
[31mbsdtar[m[m                               [31mmsggrep[m[m
[31mbundle_image[m[m                         [31mmsginit[m[m
[31mbunzip2[m[m                              [31mmsgmerge[m[m
[31mbzcat[m[m                                [31mmsgunfmt[m[m
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[31mglib-compile-schemas[m[m                 [31mrst2html5.py[m[m
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[31mgtester-report[m[m                       [31mrstpep2html.py[m[m
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[31mlz4[m[m                                  创建数组.ipynb
[35mlz4c[m[m                                 深入理解Series和DataFrame.ipynb
[35mlz4cat[m[m                               作业与练习.ipynb
[35mlzcat[m[m                                数组与矩阵运算.ipynb
[35mlzcmp[m[m

# 与sql交互后面单独说