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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

Python Web data - How to Extract HTML Tags Easily

With BeautifulSoup you can extract HTML and XML tags easily that present in Web data. Here is the best example of how to remove these.


The prime step of text analytics is cleaning. You can remove HTML tags using BeautifulSoup parser. Check out Python Logic and removing HTML tags. When analyzing web data, consider the below examples for your projects.


Python Ideas to Remove HTML tags
Python Ideas to Remove HTML tags


How I Removed Using BeautifulSoup

  1. Import BeautifulSoup
  2. Python Logic to Remove HTML tags
  3. Before and after executing the code

1. Import BeautifulSoup

import BeautifulSoup from bs4


2. Python BeautifulSoup: How to Remove HTML Tags

from bs4 import BeautifulSoup

soup = BeautifulSoup("<!DOCTYPE html><html><body><h1>My First Heading</h1><p>My first paragraph.</p></body></html>")

text = soup.get_text()

print(text)


3. Before and After Run

Before the run see the below code.


You need to import BeautifulSoup for Text analytics
Before Executing the code


After Run the tags are parsed. The means in the output tags removed.

I have shared Python sample logic on how to remove HTML tags. Also, given the package name you need. It is a useful example for text analytics.
Result after executing the code

Bottom-line of Result

Below are the steps you need for HTML tags parsing:
  1. Reads input HTML data
  2. Removes HTML tags
  3. Prints only text data

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