Because the indexes are not exactly equal, NaNs will result. Either one or both of the indexes must be changed to match. Example: mydata = mydata.set_index(DWDATA.index) The above will change the index of the ‘mydata’ DataFrame to match the index of the ‘DWDATA’ DataFrame. Since the number of rows are exactly equal for the two … Read more
This is embarrassing. The reason the compiler (GCC in this case) was optimising away the comparison and isnan returned false was because someone in my team had turned on -ffast-math. From the docs: -ffast-math Sets -fno-math-errno, -funsafe-math-optimizations, -fno-trapping-math, -ffinite-math-only, -fno-rounding-math, -fno-signaling-nans and fcx-limited-range. This option causes the preprocessor macro __FAST_MATH__ to be defined. This option … Read more
You can use isnull with mean for threshold and then remove columns by boolean indexing with loc (because remove columns), also need invert condition – so <.8 means remove all columns >=0.8: df = df.loc[:, df.isnull().mean() < .8] Sample: np.random.seed(100) df = pd.DataFrame(np.random.random((100,5)), columns=list(‘ABCDE’)) df.loc[:80, ‘A’] = np.nan df.loc[:5, ‘C’] = np.nan df.loc[20:, ‘D’] = … Read more
It claims to be 100 times faster than System.Double.IsNaN Yes, that used to be true. You are missing the time-machine to know when this decision was made. Double.IsNaN() didn’t used to look like that. From the SSCLI10 source code: public static bool IsNaN(double d) { // Comparisions of a NaN with another number is always … Read more
Perhaps you are looking for the IsNaN static function? Try something like this: if (!Double.IsNaN(Price_Foreign)) { output.Append(spacer); output.Append(String.Format(“{0,-10:C} USD”,Price_Foreign)); }
To check if the item is in the list, Python tests for object identity first, and then tests for equality only if the objects are different.1 float(“NaN”) in [float(“NaN”)] is False because two different NaN objects are involved in the comparison. The test for identity therefore returns False, and then the test for equality also … Read more
For Visual Studio I would use _isnan and _finite, or perhaps _fpclass. But if you have access to a C++11-able standard library and compiler you could use std::isnan and std::isinf.
np.nan has type float: arrays containing it must also have this datatype (or the complex or object datatype) so you may need to cast arr before you try to assign this value. The error arises because the string value ‘nan’ can’t be converted to an integer type to match arr‘s type. >>> arr = arr.astype(‘float’) … Read more
There isn’t an obvious answer because the handling depends on how you want to inform calling code of the error. (Or even if you want to interpret this as an “error”.) Some libraries/programs really don’t like raising exceptions, so do everything with signal values. In that case, returning NaN (because the value of the expression … Read more
The softmax exp(x)/sum(exp(x)) is actually numerically well-behaved. It has only positive terms, so we needn’t worry about loss of significance, and the denominator is at least as large as the numerator, so the result is guaranteed to fall between 0 and 1. The only accident that might happen is over- or under-flow in the exponentials. … Read more