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Python 如何基于.csv文件创建多个.md文件,并在每个新创建的.md文件中输入正确的.csv文件行?_Python_Excel_Pandas_Csv_Markdown - Fatal编程技术网

Python 如何基于.csv文件创建多个.md文件,并在每个新创建的.md文件中输入正确的.csv文件行?

Python 如何基于.csv文件创建多个.md文件,并在每个新创建的.md文件中输入正确的.csv文件行?,python,excel,pandas,csv,markdown,Python,Excel,Pandas,Csv,Markdown,基本上,我有一个.csv文件,其数据结构类似于以下内容: Name | Department | Committees | Years Jack | Finance | Party | 7.0 Jen | Marketing | Risk | 15.0 我希望能够根据.csv中的“姓名”列创建单独的降价文件,然后将每个人的[部门][委员会][年份]信息以以下格式写入每个降价文件: [[金融]] [[社会]] [[大学]] [[7]] 到目前为止,

基本上,我有一个.csv文件,其数据结构类似于以下内容:

Name | Department | Committees | Years

Jack | Finance    | Party      | 7.0
Jen  | Marketing  | Risk       | 15.0     
我希望能够根据.csv中的“姓名”列创建单独的降价文件,然后将每个人的[部门][委员会][年份]信息以以下格式写入每个降价文件:

  • [[金融]]
  • [[社会]]
  • [[大学]]
  • [[7]]
到目前为止,我已经能够找出如何按名称创建各个标记文件,但我无法找出如何在文件中写入正确的数据并相应地格式化它

迄今为止的代码:

import pandas as pd
import csv

data = pd.read_csv("Employee_Directory.csv")
names = data.Name.to_list()

for n in names:
    name = n.split(", ")
   
    file_name = name[0].replace("\n", "") + ".md"

    new_file = open(file_name, "w+")
    new_file.write = ""
    new_file.close()

print("Success")
任何帮助都将不胜感激。

我想:

import pandas as pd

# Create a dataFrame from csv file
data = pd.read_csv("Employee_Directory.csv", sep=',', engine='python', encoding="utf- 
8").fillna('')

# Filtering out unwanted characters
data['Committees']=data['Committees'].str.replace("<br>","]] [[")
data['Committees']=data['Committees'].str.replace("-"," ")
data['Associations 1']=data['Associations 1'].str.replace("<br>"," ")
data['Associations 2']=data['Associations 2'].str.replace("<br>"," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace("<br>","]] [[")
data['I am a Resource For']=data['I am a Resource For'].str.replace("+","]] [[")
data['I am a Resource For']=data['I am a Resource For'].str.replace("-"," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace("/"," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace(":"," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace(")"," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace("("," ")
data['I am a Resource For']=data['I am a Resource For'].str.replace(",","]] [[")
data['Education 1']=data['Education 1'].str.replace("<br>"," ")
data['Education 2']=data['Education 2'].str.replace("<br>"," ")

# Set the names column to a list
names = data.values.tolist()

# Loop through each name, create .md file, set contents to string
for name in names:
    fname = str(name[0])
    file_name = f'{fname}.md'
    dept = str(name[1])
    comm = str(name[2])
    assoc_one = str(name[3])
    assoc_two = str(name[4])
    canbim = str(name[5])
    resource_for = str(name[6])
    #skills = str(name[7])
    edu_one = str(name[8])
    edu_two = str(name[9])
    #degrees = str(name[10])
    years = str(name[11])

    # Write Contents to .md formatted as required
    with open(file_name, 'w', encoding="utf-8") as f:
        f.write(f' | Name: {fname} | \n | Department: [[{dept}]] | \n | Committees: 
        [[{comm}]] | \n | Associations 1: [[{assoc_one}]] | \n | Associations 2: 
        [[{assoc_two}]] | \n | CanBIM Level: [[{canbim}]] | \n | I am a resource for: 
        [[{resource_for}]] | \n | Education 1: [[{edu_one}]] | \n | Education 2: 
        [[{edu_two}]] | \n | [[{years} Years with Studio]] |')
        f.close()
    print(f'{file_name} saved.')
将熊猫作为pd导入
#从csv文件创建数据帧
data=pd.read\u csv(“Employee\u Directory.csv”,sep=',,engine='python',encoding='utf-
8“.fillna(“”)
#过滤掉不需要的字符
数据['Committees']=数据['Committees'].str.replace(“
”,“]][”) 数据['Committees']=数据['Committees'].str.replace(“-”,”) 数据['Associations 1']=data['Associations 1'].str.replace(“
”,“”) 数据['Associations 2']=数据['Associations 2'].str.replace(“
”,“”) data['I是']=data['I是'].str.replace(“
”,“][]”)的资源 data['I是']=data['I是'].str.replace(“+”,“]][]”)的资源 data['I是']]的资源=data['I是'].str.replace(“-”,”“) data['I是']]的资源=data['I是'].str.replace(“/”,“”) data['I是']]的资源=data['I是'].str.replace(“:”,”“) data['I是']]的资源=data['I是'].str.replace(“)”,“”) data['I是']]的资源=data['I是'].str.replace(“,”) data['I是']=data['I是'].str.replace(“,”,“]][]”)的资源 数据['Education 1']=数据['Education 1'].str.replace(“
”,“”) 数据['Education 2']=数据['Education 2'].str.replace(“
”,“”) #将“名称”列设置为列表 名称=data.values.tolist() #循环遍历每个名称,创建.md文件,将内容设置为字符串 对于名称中的名称: fname=str(名称[0]) 文件名=f'{fname}.md' dept=str(名称[1]) comm=str(名称[2]) assoc_one=str(名称[3]) assoc_two=str(名称[4]) canbim=str(名称[5]) 资源\u for=str(名称[6]) #skills=str(名称[7]) edu_one=str(名称[8]) edu_two=str(名称[9]) #度=str(名称[10]) 年份=str(名称[11]) #将内容写入.md,并按要求格式化 打开(文件名为“w”,编码为“utf-8”)作为f: f、 写下(f’|姓名:{fname}}\n |部门:[[{dept}]]\n |委员会: [{comm}]|\n |协会1:[[{assoc|u one}]|\n |协会2: [{assoc_two}].\n|CanBIM级别:[[{CanBIM}].\n|我是以下方面的资源: 教育1: [[{edu_two}].\n |[[{years}年工作室]].') f、 关闭() 打印(f'{file_name}已保存')