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ํŒŒ์ด์ฌ pandas ์—ฌ๋Ÿฌ ํด๋” ๋‚ด csv ๋ถˆ๋Ÿฌ์˜ค๊ธฐ ๋ณธ๋ฌธ

๐Ÿ‘ฉ‍๐Ÿ’ป ์ปดํ“จํ„ฐ ๊ตฌ์กฐ/etc

ํŒŒ์ด์ฌ pandas ์—ฌ๋Ÿฌ ํด๋” ๋‚ด csv ๋ถˆ๋Ÿฌ์˜ค๊ธฐ

์ง•์ง•์•ŒํŒŒ์นด 2022. 12. 5. 16:43
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์—ฌ๋Ÿฌ ํด๋” ์•ˆ์— csv ๋ถˆ๋Ÿฌ์˜ค๊ธฐ

์•ฝ๊ฐ„ ๋…ธ๊ฐ€๋‹ค... ใ…‹

 

ํด๋”๋งˆ๋‹ค ๋‚ ์งœ๋ณ„๋กœ ๋‹ค๋ฅธ csv ํŒŒ์ผ์ด ์žˆ๊ธฐ ๋•Œ๋ฌธ์—

๊ฐ™์€ ํŒŒ์ผ๋ช…์„ ๊ฐ€์ง„ csv ํŒŒ์ผ๋ผ๋ฆฌ concat ํ•  ์˜ˆ์ •~~~~

 

๐Ÿธ ํด๋” load

# Load the data
forder_list = os.listdir("./DATA")
forder_list

 

 

๐Ÿธ csv ๊ฒฝ๋กœ ๋ฆฌ์ŠคํŠธ ์™„์„ฑ

csv1 = []
csv2 = []
csv3 = []
csv4 = []
csv5 = []
csv6 = []

for forder in forder_list :
    paths = "./DATA/" + forder + "/"
    # print(paths)
    file_path = sorted(os.listdir(paths))
    # print(file_path)
    
    csv1.append(paths + file_path[0])
    csv2.append(paths + file_path[1])
    csv3.append(paths + file_path[2])
    csv4.append(paths + file_path[3])
    csv5.append(paths + file_path[4])
    csv6.append(paths + file_path[5])

 

 

๐Ÿธ ๊ฐ™์€ csv ๋ผ๋ฆฌ ํ•˜๋‚˜์˜ dataframe์œผ๋กœ concat ํ•˜๊ธฐ (axis = 0)

allData = [] # ์ฝ์–ด ๋“ค์ธ csvํŒŒ์ผ ๋‚ด์šฉ์„ ์ €์žฅํ•  ๋นˆ ๋ฆฌ์ŠคํŠธ๋ฅผ ํ•˜๋‚˜ ๋งŒ๋“ ๋‹ค

for file in csv1:
    df = pd.read_csv(file) # for๊ตฌ๋ฌธ์œผ๋กœ csvํŒŒ์ผ๋“ค์„ ์ฝ์–ด ๋“ค์ธ๋‹ค
    allData.append(df) # ๋นˆ ๋ฆฌ์ŠคํŠธ์— ์ฝ์–ด ๋“ค์ธ ๋‚ด์šฉ์„ ์ถ”๊ฐ€ํ•œ๋‹ค

์–ด์ฐจํ”ผ ๊ฐ™์€ ์†์„ฑ์„ ๊ฐ€์ง„ csv ํŒŒ์ผ์ด๋ผ axis = 0 ์œผ๋กœ concat

dataCombine = pd.concat(allData, axis=0, ignore_index=True)

์™„์„ฑ~

 

 

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