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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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Scraping Website: How to Write a Script in Python

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Here's a python model script to scrape a website using the BeautifulSoup.


Scrapping website

Python script

The logic below uses BeautifulSoup Package for web scraping.


import requests

from bs4 import BeautifulSoup

url = "https://www.example.com"

response = requests.get(url)

soup = BeautifulSoup(response.text, "html.parser")

# Print the title of the webpage

print(soup.title.text)

# Print all the links in the webpage

for link in soup.find_all("a"):

    print(link.get("href"))



In this script, we first import the Requests and Beautiful Soup libraries. We then define the URL we want to scrape and use the Requests library to send a GET request to that URL. We then pass the response text to Beautiful Soup to parse the HTML contents of the webpage.

We then use Beautiful Soup to extract the title of the webpage and print it to the console. We also use a for loop to find all the links in the webpage and print their href attributes to the console.

This is just a basic example, but you can use Beautiful Soup to extract any other HTML elements you want from the webpage.

References

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