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AI Learning Python

AI & Python #8: Pandas Functions that Data Analysts Use 60% of the Time

According to Forbes, data scientists and analysts spend 60% of their time on cleaning and organizing data. This shows how important data cleaning and data wrangling are in a project. Data cleaning consists in cleaning the data we’ll use, so we don’t have incorrect, corrupted, duplicate, or incomplete data. Real-world data isn’t as clean as

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AI Learning Python

AI & Python #7: Stop Overusing “+” to Join Strings in Python

One common task data analysts have to deal with when collecting and cleaning data is working with strings. This involves formatting as well as joining strings (also known as string concatenation). Joining strings in Python   is as simple as using the plus operator +. You’ve probably used the code below hundreds of times to join

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