๊ด€๋ฆฌ ๋ฉ”๋‰ด

yeon's ๐Ÿ‘ฉ๐Ÿป‍๐Ÿ’ป

[ํ”„๋žœ์ฐจ์ด์ฆˆ ์ž…์ ๋ถ„์„] ์ „์ฒ˜๋ฆฌ ํŒŒ์ผ ์ €์žฅํ•˜๊ธฐ ๋ณธ๋ฌธ

Computer ๐Ÿ’ป/๋ฐ์ดํ„ฐ ๋ถ„์„

[ํ”„๋žœ์ฐจ์ด์ฆˆ ์ž…์ ๋ถ„์„] ์ „์ฒ˜๋ฆฌ ํŒŒ์ผ ์ €์žฅํ•˜๊ธฐ

yeon42 2021. 8. 5. 00:05
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- ํ”„๋žœ์ฐจ์ด์ฆˆ ๋งค์žฅ์ด ์–ผ๋งˆ๋‚˜ ๋ชจ์—ฌ ์žˆ๋Š”์ง€ or ์–ผ๋งˆ๋‚˜ ํฉ์–ด์ ธ ์žˆ๋Š”์ง€ ์ง€๋„์— ํ‘œ์‹œํ•ด๋ณด๊ธฐ

ex) ๋ฐฐ์Šคํ‚จ๋ผ๋นˆ์Šค & ๋˜ํ‚จ๋„๋„ˆ์ธ 

ex) ํŒŒ๋ฆฌ๋ฐ”๊ฒŒํŠธ & ๋šœ๋ ˆ์ฅฌ๋ฅด

 

 

 


 

 

 

6. ์ƒ‰์ธ์œผ๋กœ ์„œ๋ธŒ์…‹ ๊ฐ€์ ธ์˜ค๊ธฐ

 

6.1 ์„œ์šธ๋งŒ ๋”ฐ๋กœ ๋ณด๊ธฐ

 

  • ์‹œ๋„๋ช… ์ด ์„œ์šธ ์ธ ๋ฐ์ดํ„ฐ๋งŒ
df_seoul = df[df["์‹œ๋„๋ช…"] == "์„œ์šธํŠน๋ณ„์‹œ"].copy()

 

 

 


 

 

7. ํŒŒ์ผ๋กœ ์ €์žฅํ•˜๊ธฐ

- ์ „์ฒ˜๋ฆฌํ•œ ํŒŒ์ผ ์ €์žฅํ•ด๋‘๋ฉด ์žฌ์‚ฌ์šฉ ๊ฐ€๋Šฅ

 

df_seoul.to_csv("seoul_open_store.csv")

-> "seoul_open_store.csv" ๋ผ๋Š” ํŒŒ์ผ์ด ์ƒ์„ฑ๋จ!

but, ๋งจ ์•ž์— Unnamed:0 ์ด๋ผ๋Š” index๊ฐ’์„ ๋‚˜ํƒ€๋‚ด๋Š” ์ปฌ๋Ÿผ์ด ์ƒ๊น€

 

 

 

df_seoul.to_csv("seoul_open_store.csv", index=False)

  - ์ด์ œ ์ธ๋ฑ์Šค ์—†์•ฐ

 

 

- ํŒŒ์ผ ์ฝ์„ ๋•Œ๋Š” : pd.read_csv("ํŒŒ์ผ์ด๋ฆ„")

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