我有一个datframe为：
data=[[0,1,5],
[0,1,6],
[0,0,8],
[0,0,10],
[0,1,12],
[0,0,14],
[0,1,16],
[0,1,18],
[1,0,2],
[1,1,0],
[1,0,1],
[1,0,2]]
df = pd.DataFrame(data,columns=['KEY','COND','VAL'])
对于RES1，我想创建一个计数器变量RES，其中COND == 1。组中第一个KEY的RES值与VAL相同（我可以以某种方式使用cumcount（））。
对于RES2，我只想将缺少的值填充为先前的值。(df.fillna(method='ffill'))， 我在想..
KEY COND VAL RES1 RES2
0 0 1 5 5 5
1 0 1 6 6 6
2 0 0 8 6
3 0 0 10 6
4 0 1 12 7 7
5 0 0 14 7
6 0 1 16 8 8
7 0 1 18 9 9
8 1 0 2 2 2
9 …我正在尝试将数据框过滤为：
a= a[~(b['var1'].isin(c['var2']))]
但出现以下错误：
"Unalignable boolean Series provided as "
pandas.core.indexing.IndexingError: Unalignable boolean Series provided as indexer (index of the boolean Series and of the indexed object do not match).
我理解该声明：
print(~(b['var1'].isin(c['var2'])) [:10])
返回一个布尔掩码的系列，这可能是不可接受的。所以，我尝试将 loc 用作：
a= a.loc[:, ~(b['var1'].isin(c['var2']))]
但我遇到了同样的错误。我在这里缺少什么？任何意见将不胜感激。
谢谢
Bottomline, I want In a comparison, NaN numeric values to be lower than any other numeric value.
Lets say I have s1 and s2,
s1 = pd.Series([1, 3, np.nan, 5, np.nan, -1, np.nan])
s2 = pd.Series([2, 1, np.nan, np.nan, 2, np.nan, -1])
When I compare them as s1 < s2 then I want the following behavior:
Out:
0 True
1 False
2 False
3 False
4 True
5 False
6 True