df.cumsum(axis=None, skipna=True, args, kwargs) ๋ˆ„์ ํ•ฉ
df.cumprod(axis=None, skipna=True, args, kwargs) ๋ˆ„์ ๊ณฑ


axis : ๋ˆ„์ ํ•ฉ/๋ˆ„์ ๊ณฑ์„ ๊ตฌํ•  ์ถ•์„ ์ง€์ •ํ•ฉ๋‹ˆ๋‹ค.
skipna : ๊ฒฐ์ธก์น˜๋ฅผ ๋ฌด์‹œํ• ์ง€ ์—ฌ๋ถ€ ์ž…๋‹ˆ๋‹ค

์˜ˆ์‹œ

df = pd.DataFrame({'col1':[2,-2,4,5,6,8],'col2':[3,4,np.NaN,7,4,5]})
print(df)
   col1  col2
0     2   3.0
1    -2   4.0
2     4   NaN
3     5   7.0
4     6   4.0
5     8   5.0

 

๋ˆ„์ ํ•ฉ cumsum() 

print(df.cumsum())
 col1  col2
0     2   3.0
1     0   7.0
2     4   NaN
3     9  14.0
4    15  18.0
5    23  23.0

 

๋ˆ„์ ๊ณฑ cumprod()

print(df.cumprod())
   col1    col2
0     2     3.0
1    -4    12.0
2   -16     NaN
3   -80    84.0
4  -480   336.0
5 -3840  1680.0

 

skipna ์ธ์ˆ˜์˜ ์‚ฌ์šฉ

print(df.cumsum(skipna=False))
   col1  col2
0     2   3.0
1     0   7.0
2     4   NaN # NaN ๋“ฑ์žฅ๋ถ€ํ„ฐ ๊ณ„์‚ฐํ•  ์ˆ˜ ์—†์œผ๋ฏ€๋กœ NaN ๋ฐ˜ํ™˜
3     9   NaN
4    15   NaN
5    23   NaN

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