Showing posts with the label Access Modifiers

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How to Check Column Nulls and Replace: Pandas

Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

3 Exclusive Access Modifiers in Python

Here are three access modifiers in Python - Public, Protect, and Private. Access modifiers control the access to a variable/or method.  You may have a question that does python supports access modifiers? The answer is yes. In general, all the variables/or methods are public. Which means accessible to other classes. The private and protect access modifiers will have some rules. And the notation for protect and private are different. The single underscore is for protected and the double underscore is for private. Here is how to find Python list frequent items. Differences between Public, Protect and Private Public access modifier Public variables are accessible outside the class. So in the output, the variables are displayed. class My_employee:     def __init__(self, my_name, my_age):         self.my_name = my_name  #public         self.my_age = my_age   # public my_emp = My_employee('Raj',34) print(my_emp.my_name) print(my_emp.my_age) my_emp.my_name = 'Rohan' print(my_em