複数ファイル形式(CSV、XML、JSON)

1. CSV

CSVファイルとPandas

# Data -> CSV file
import pandas as pd

df=pd.DataFrame(rows, columns=fields)
df.to_csv('pandas.csv',index=False)

# CSV file -> DataFrame
df = pd.read_csv('pandas.csv')
df.head()

2. XML

XMLファイルの作成

XMLグループ

BeautifulSoupによるグループ化

# 파일의 title 태그만 추출하기

from bs4 import BeautifulSoup
import os

path = os.getenv("HOME") + "/aiffel/ftext/data/books.xml"  
with open(path, "r", encoding='utf8') as f:
    booksxml = f.read() 
    #- 파일을 문자열로 읽기
 
soup = BeautifulSoup(booksxml,'lxml') 
#- BeautifulSoup 객체 생성 : lxml parser를 이용해 데이터 분석

for title in soup.find_all('title'): 
#-  태그를 찾는 find_all 함수 이용
	
    print(title.get_text())
    print(title)

3. JSON

# 예시
person = {
      "first name" : "Yuna",
      "last name" : "Jung",
      "age" : 33,
      "nationality" : "South Korea",
      "education" : [{"degree":"B.S degree", "university":"Daehan university", 
      "major": "mechanical engineering", 
      "graduated year":2010}]
       } 

JSONパーティション

import json

person = {
      "first name" : "Yuna",
      "last name" : "Jung",
      "age" : 33,
      "nationality" : "South Korea",
      "education" : [{"degree":"B.S degree", "university":"Daehan university", "major": "mechanical engineering", "graduated year":2010}]
       } 

with open("person.json", "w") as f:
    json.dump(person , f)

import json

with open("person.json", "r", encoding="utf-8") as f:
    contents = json.load(f)
    print(contents["first name"])
    print(contents["nationality"])
    
# 출력 결과
Yuna
South Korea