[英]Check if value is in Pandas dataframe column
I've having an issue checking is a value is in the following dataframe:我有一个问题检查是一个值在以下 dataframe 中:
index![]() |
open![]() |
high![]() |
SignalEMA25M50M![]() |
PositionEMA25M50M![]() |
---|---|---|---|---|
2021-03-30 05:35:00 ![]() |
0.000059 ![]() |
0.000059 ![]() |
0 ![]() |
-1.0 ![]() |
2021-03-30 05:40:00 ![]() |
0.000059 ![]() |
0.000059 ![]() |
0 ![]() |
0.0 ![]() |
2021-03-30 05:45:00 ![]() |
0.000059 ![]() |
0.000059 ![]() |
0 ![]() |
0.0 ![]() |
i am trying to simply return true if the PositionEMA25M50M contains -1.0如果 PositionEMA25M50M 包含 -1.0,我试图简单地返回 true
i have tried:我努力了:
if -1.0 in indicator_5min_df.PositionEMA25M50M:
print('true')
else:
print('false')
however this returns false every time... i assume this is something to do with PositionEMA25M50M being of type float64 however i've also tried但是这每次都返回错误...我认为这与 PositionEMA25M50M 的类型为 float64 但我也尝试过
if np.float64(-1.0) in indicator_5min_df.PositionEMA25M50M:
print('true')
else:
print('false')
which has given me the same result...这给了我同样的结果......
any ideas how i can fix this?有什么想法可以解决这个问题吗?
You don't need a if
loop.您不需要
if
循环。 You can directly use Series.eq
with any
to check if any row has -1
for this column:您可以直接将
Series.eq
与any
一起使用来检查该列是否有任何行具有-1
:
In [990]: df['PositionEMA25M50M'].eq(-1).any()
Out[990]: True
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