What is Natural Language Processing (NLP)?
Natural language processing (NLP) is a branch of artificial intelligence focused on computer science. NLP’s primary goal is to give computers the ability to understand written text, human language, and analyze large corpuses of natural language data.
- Go to textrazor.com so you can set up your account.
- Click “Free API Key” and go through the process of entering your information and verifying your email so you can grab your free API key.
- Install TextRazor and other Python Libraries
https://colab.research.google.com/drive/1kzs8pfC37XL3cN_BhjiaKEG1V8j2fbHV?usp=sharing
- Run the first cell to install and import TextRazor
Run the first cell to install and import TextRazor and other needed Python libraries.
- Insert TextRazor API Key and Run
- Create TextRazor Class and Enter URL to Analyze.
- Create Dataframe with TextRazor Entities for URL
- Visualize TextRazor Top Entities using Matplotlib & Display values in Pandas dataframe
Analyze SERP Results using TextRazor (TextRazor V2)
- Install and import Advertools
- Insert Keyword and Crawl Page 1 of SERPs
https://developers.google.com/custom-search/v1/overview#api_key
Now enter your query, search engine ID, and Google Search API key
- Save Rankings to CSV file
- Crawl and Analyze Rankings with TextRazor API
- Group Entities by URL and Count Entity Mentions
- Visualize Entities Using Plotly
Bulk Canonical Tag Generator Using Python
A canonical tag (or rel=canonical) is a small piece of HTML code that helps search engines to determine the “main” version of the page from the rest of the pages that are identical or very similar to it.
Step 1:
Create a folder on desktop. And –
Create an xlsx file, rename it to “input”
Open the input file and create 2 column –
Take the URLs from screaming frog, and paste it on url_column tab.(Only relevant URL or desired URLs)
Now, paste the same urls on the canonical column for self-referencing canonical tag, or you can set any desired canonical for desired url.
Now save it.
Step 2:
Copy the this python code and save it on that folder –
import openpyxl
def generate_canonical_tags(filename):
# Load the XLSX file
workbook = openpyxl.load_workbook(filename)
sheet = workbook.active
# Get the maximum number of rows in the sheet
max_row = sheet.max_row
# Define the column indices for relevant data
url_column = 1
canonical_column = 2
# Iterate over the rows and generate the Canonical Tags
canonical_tags = []
for row in range(2, max_row + 1): # Start from row 2, assuming headers are in row 1
url = sheet.cell(row=row, column=url_column).value
canonical = sheet.cell(row=row, column=canonical_column).value
if url and canonical:
canonical_tag = f'<link rel=”canonical” href=”{canonical}” />’
canonical_tags.append((url, canonical_tag))
return canonical_tags
# Example usage
input_filename = ‘input.xlsx’
output_filename = ‘output.xlsx’
# Generate Canonical Tags
canonical_tags = generate_canonical_tags(input_filename)
# Create a new workbook and sheet for output
output_workbook = openpyxl.Workbook()
output_sheet = output_workbook.active
# Write the headers
output_sheet.cell(row=1, column=1).value = ‘URL’
output_sheet.cell(row=1, column=2).value = ‘Canonical Tag’
# Write the generated Canonical Tags to the sheet
for row, (url, canonical_tag) in enumerate(canonical_tags, start=2):
output_sheet.cell(row=row, column=1).value = url
output_sheet.cell(row=row, column=2).value = canonical_tag
# Save the output workbook to a file
output_workbook.save(output_filename)
print(f”Canonical Tags generated and saved to ‘{output_filename}’ successfully!”)
Rename it “canonical”
Like this –
Now open anaconda prompt –
And select your folder using cd command –
And type – python canonical.py
The file is generated for bulk canonical tags –
Now we can implement those tags on head section of desired pages.
