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How to Check Column Nulls and Replace: Pandas

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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
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6 Exclusive List and Tuple Differences in Python

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Here're quick differences between List and Tuple


Here're the quick differences between Tuple and List in Python. These are helpful for interviews and your project.

Tuple and List differences

List

  • Comma-separated elements inside a square bracket [] make a list.
  • The elements are indexed, which starts from '0'
  • These you need to enclose in a single quote and separate by a comma.
  • It can contain another list, which is called a NESTED list.
  • Use type() function to get the type of data it is.
  • The list is mutable (you can change the data). The objects (elements) can be of different data types. Here're examples on the List.

Tuple

  • The elements comma-separated and enclosed in parenthesis () 
  • The elements are indexed, which starts from '0'
  • It can have heterogeneous data (integer, float, string, list, etc.)
  • It is immutable. So you can't change the elements.
  • Use the type() function to get the type of data it is. 
  • Here're examples of Tuple.

List Example

#Illustration of creating a list 
new_list=[1, 2, 3, 4] 
print(new_list) 


# Homogeneous data elements 
new_list1=[1, "John", 55.5] 
print(new_list1) 


# Heterogeneous data elements 
new_list2=[111, [1, "Clara", 75.5]] 
# Nested list 
print(new_list2)


Output



[1, 2, 3, 4]
[1, ‘John’, 55.5]
[111, [1, ‘Clara’, 75.5]]



Tuple Example


#Illustration of unpacking a tuple 
 new_tuple2=(111, [1, "Clara", 75.5], (2, "Simon", 80.5)) 

# Nested tuple 
print(new_tuple2) x, y, z=new_tuple2 
print(x) 
print(y) 
print(z) 


Output



111
[1, ‘Clara’, 75.5]
(2, ‘Simon’, 80.5)

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