shoo. 2023. 9. 13. 19:39

info() ํ•จ์ˆ˜๋Š” pandas DataFrame์— ๋Œ€ํ•œ ์š”์•ฝ ์ •๋ณด๋ฅผ ์ถœ๋ ฅํ•˜๋Š”๋ฐ ์‚ฌ์šฉ๋ฉ๋‹ˆ๋‹ค. ์ด ํ•จ์ˆ˜๋Š” DataFrame์˜ ํฌ๊ธฐ, ์ปฌ๋Ÿผ ์ด๋ฆ„, ๋ฐ์ดํ„ฐ ํƒ€์ž…, ๋น„์–ด์žˆ์ง€ ์•Š์€ ๊ฐ’์˜ ๊ฐœ์ˆ˜ ๋“ฑ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

 

import pandas as pd

# ์ƒ˜ํ”Œ ๋ฐ์ดํ„ฐ ์ƒ์„ฑ
data = {
    'Name': ['John', 'Anna', 'Peter', 'Linda'],
    'Age': [28, 24, 35, 32],
    'City': ['New York', 'Paris', None, 'Berlin']
}
df = pd.DataFrame(data)

# DataFrame ์ •๋ณด ์ถœ๋ ฅ
df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 3 columns):
 #   Column  Non-Null Count Dtype 
---  ------  -------------- ----- 
 0   Name    4 non-null      object
 1   Age     4 non-null      int64 
 2   City    3 non-null      object
dtypes: int64(1), object(2)
memory usage: XXX bytes

์ด ๊ฒฐ๊ณผ๋Š” ์ด ๋„ค ๊ฐœ์˜ ํ–‰๊ณผ ์„ธ ๊ฐœ์˜ ์—ด์ด ์žˆ์œผ๋ฉฐ ๊ฐ ์—ด์˜ ๋ฐ์ดํ„ฐ ํƒ€์ž…๊ณผ ๋น„์–ด์žˆ์ง€ ์•Š์€ ๊ฐ’์˜ ์ˆ˜๋ฅผ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. City ์—ด์—์„œ ํ•˜๋‚˜์˜ ๊ฒฐ์ธก๊ฐ’(None)์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

๋”ฐ๋ผ์„œ info() ํ•จ์ˆ˜๋Š” ์ฃผ๋กœ ๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌ ๋‹จ๊ณ„์—์„œ DataFrame์˜ ์ „๋ฐ˜์ ์ธ ๊ตฌ์กฐ์™€ ๊ฒฐ์ธก๊ฐ’ ์—ฌ๋ถ€ ๋“ฑ์„ ํŒŒ์•…ํ•˜๋Š”๋ฐ ์œ ์šฉํ•˜๊ฒŒ ์‚ฌ์šฉ๋ฉ๋‹ˆ๋‹ค.