我有一个看起来像这样的 pandas DataFrame:
I've got a pandas DataFrame that looks like this:
sum
1948 NaN
1949 NaN
1950 5
1951 3
1952 NaN
1953 4
1954 8
1955 NaN
我想只在开头和结尾截断 NaN
(即只保留从 1950 到 1954 的值,包括 NaN
).我已经尝试过 .isnull()
和 dropna()
,但不知何故我找不到合适的解决方案.有人可以帮忙吗?
and I would like to cut off the NaN
s at the beginning and at the end ONLY (i.e. only the values incl. NaN
from 1950 to 1954 should remain).
I already tried .isnull()
and dropna()
, but somehow I couldn't find a proper solution.
Can anyone help?
使用内置的first_valid_index
和 last_valid_index
它们是专门为此设计的,并对你的 df 进行切片:
Use the built in first_valid_index
and last_valid_index
they are designed specifically for this and slice your df:
In [5]:
first_idx = df.first_valid_index()
last_idx = df.last_valid_index()
print(first_idx, last_idx)
df.loc[first_idx:last_idx]
1950 1954
Out[5]:
sum
1950 5
1951 3
1952 NaN
1953 4
1954 8
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