In this video we will be covering the basics of N8N for beginners. We will talk about AI Agents, RAG, workflows and much more! Also if you need help with any Data or N8N needs, I’m taking on customers! If you are brand new to N8N you can sign up here https://youtu.be/8s_no0yQkLo What is N8N […]
N8N Ai Agent
Using AI Agents is critical if you want to build out extensive workflows that can get tasks done. In this lesson we will go over the AI Agent and all its components. If you would rather watch a video instead of reading an article, our YouTube video is linked down below. Also if you need […]
N8N Gmail
Gmail is used in a ton of N8N workflows and in this article we are going to cover some of the most popular usecases. Items like extracting information from emails, auto forwarding emails, uploading pdfs to google drive, and much more. If you prefer to watch a YouTube video over reading an article, it is […]
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
Here we define a dataset containing records of eight runners. Each entry includes: The runners first and last name. Thier finish times in hours for threee race types: Marathon 50-miler 100-miler The date of their last race and a running_clud_id showing which running club each runner belongs to. Next, we create a tabular structure with […]
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 […]