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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

Python Abstract Classes to Learn Quickly

Here's the best example of how to understand the abstract classes of python quickly. An abstract class means it is a skeleton. You cannot instantiate abstract classes.

For Example:

The abstract class name is 'dog'

o = dog()

It gives an error. Since the 'dog' is an abstract class.

I am sharing with you a clear understanding of abstract class. So that you can tell confidently about these classes.

Here is the beautiful answer with syntax and examples of the Python abstract class.

The syntax for Abstract Class

from abc, import ABC, abstractmethod 
class <class name>(ABC):
def <method name>(): 
#abstract class definition

Python Abstract Class Explanation

from abc import ABC, abstractmethod
class AbsBaseClass(ABC):
def __init__(self):
print("Abstract class")
def abMeth(self):
def conMeth(self):
print("I'm a concrete method")
class Derived(AbsBaseClass):
def abMeth(self):
print("I'm redefined")



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