Pandas:仅在数据帧的开头和结尾删除 NaN

2022-01-11 00:00:00 python pandas dataframe time-series nan

问题描述

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 NaNs 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?

解决方案

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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