Scraping the top websites for search terms can serve many purposes. Some companies may give this to sales members to reach out to potential clients, while others may use it to track SEO competitors. In this N8N lesson, I’ll show you how to scrape the Google Search Engine Results Page (SERP) with the help of […]
n8n LinkedIn Lead Generator
One of the best benefits of using N8N is the ability to integrate in APIs like that of Apify with ease. In just a few nodes we can scrape LinkedIn (a site which is very hard to scrape) and send data into a Google Sheet. Integrations like this often save sales teams hours each week […]
pandas create dataframe
In this tutorial, we’ll explore multiple ways to create a Pandas DataFrame from various Python data structures like lists, dictionaries, NumPy arrays, and more. It’s based on a tutorial published down below on our YouTube channel. First let’s import pandas for data manipulation and analysis. We’ll also import supporting libraries like NumPy and JSON for […]
python standard error of the mean
Example 1 – Manual Calculation – Strikeouts Per Season Example 2 Scipy Example 3 Marathon Times Example viz
python quantiles statistics
In Python, a quantile is a statistical term used to describe a point or value below which a certain proportion of the data falls. It means a quntile split data into intervals. We start by importing numpy and pandas. numpy is used for high-performance numerical computation. Pandas is used for data manipulation, data analysis and […]
Python Pandas Data Cleaning
https://www.espncricinfo.com/records/highest-career-batting-average-282910 Here, we read the CSV file names ‘CricketTestMatchData.csv’ into a DataFrame called df using the read_csv. Here, we check for missing null values in the DataFrame df. It returns a Boolean result for each column. It returns True if the colun has any missing values and False if it doesn’t. This line filters the […]
Pandas Columns
Pandas Dataframes are composed of Rows and Columns. In this guide we are going to cover everything you need to know about working with columns. The article is based on a tutorial we published on our YouTube channel. Feel free to check it out below. Let’s start with importing in Pandas and NumPy. Here we […]
Pandas Resample
The .resample() method in pandas works similarly to .groupby(), but it is specifically designed for time-series data. It groups data into defined time intervals and then applies one or more functions to each group. This method is useful for both upsampling—where missing data points can be filled or interpolated—and downsampling, which involves aggregating data over […]
Python Pandas JSON
JSON (JavaScript Object Notation) is a lightweight, human-readable data interchange format that is widely used for both data storage and transfer. It is structured using key-value pairs and supports various data types, including strings, numbers, booleans, arrays, and nested objects. JSON is a standard format commonly used in APIs and web data, which makes it […]
beautifulsoup pagination
import requests – Allows us to make HTTP requests to web pages. from bs4 import BeautifulSoup –It is used to parse and extract data from HTML content. import pandas as pd – It is used for organizing and manipulating data in table format. import re – It enables pattern matching using regular expressions. from time […]