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  2. How to check if any value is NaN in a Pandas DataFrame

    stackoverflow.com/questions/29530232

    Alternatively, check the sum: np.isnan(df.values).sum() # 2 np.isnan(df.values).sum() > 0 # True Series.hasnans You can also iteratively call Series.hasnans. For example, to check if a single column has NaNs, df['A'].hasnans # True And to check if any column has NaNs, you can use a comprehension with any (which is a short-circuiting operation).

  3. print('DataFrame is empty!') df.empty checks whether one of the axes (index or columns) is of length 0. In other words, it does the following check: len(df.index) == 0 or len(df.columns) == 0. @Zero's suggestion only checks if the index is of length 0, while Sven's suggestion only checks if the columns are of length 0.

  4. HAVING COUNT(*) > 1. The GROUP BY clause groups the rows into groups by values in both name and email columns. Then, the COUNT () function returns the number of occurrences of each group (name,email). Then, the HAVING clause keeps only duplicate groups, which are groups that have more than one occurrence. 2.

  5. 14. To check if there is a GPU available: torch.cuda.is_available() If the above function returns False, you either have no GPU, or the Nvidia drivers have not been installed so the OS does not see the GPU, or the GPU is being hidden by the environmental variable CUDA_VISIBLE_DEVICES.

  6. 1. In Python, you can use the built-in isinstance() function to check if an object is of a given type, or if it inherits from a given type. To check if the object o is of type str, you would use the following code: if isinstance(o, str): # o is of type str. You can also use type() function to check the object type.

  7. Depending on the situation you can check with isinstance what kind of object you have, and then use the corresponding attributes. With the introduction of abstract base classes in Python 2.6/3.0 this approach has also become much more powerful (basically ABCs allow for a more sophisticated way of duck typing).

  8. Check if a given key already exists in a dictionary

    stackoverflow.com/questions/1602934

    I would recommend using the setdefault method instead. It sounds like it will do everything you want. >>> d = {'foo':'bar'} >>> q = d.setdefault('foo','baz') #Do not override the existing key >>> print q #The value takes what was originally in the dictionary bar >>> print d {'foo': 'bar'} >>> r = d.setdefault('baz',18) #baz was never in the dictionary >>> print r #Now r has the value supplied ...

  9. If you need to check what is alaready installed version of any packages you can simply use Pip command as below. Template. pip show <PACKAGE_NAME> | grep Version or pip show <PACKAGE_NAME> with pip3. pip3 show <PACKAGE_NAME> | grep Version or pip3 show <PACKAGE_NAME> Example

  10. The null check will be at least a thousand times faster (probably many thousands). For the path of execution to get into the catch block an exception has to have been raised which means generating a stack trace etc etc. I don't know for sure but the null check almost certainly drops to a native instruction so it's as close to instant as you can ...

  11. How can I check if a checkbox in a checkbox array is checked using the id of the checkbox array? I am using the following code, but it always returns the count of checked checkboxes regardless of ...