Python in Excel - Total Data Analysis

In this lesson of the Python in Excel course, you're gonna learn how to import Python libraries into Microsoft Excel. Plus, you'll find out which Python libraries are already pre-loaded in Excel, so you don't even have to bother importing them.

In this lesson of the Python in Excel course, you'll learn how to create a DataFrame using Pandas so you can kick off your data analysis in Microsoft Excel.

In this lesson of the Python in Excel course, we're going to learn how to create our first charts with Python in Microsoft Excel using seaborn. We'll make bar charts, scatter plots, violin plots, heatmaps, and more. Sounds exciting, doesn't it?

In this lesson of the Python in Excel course, you're gonna get to know the two fundamental elements of Pandas: DataFrames and Series. You'll learn their main features and get to use some of their most common methods like 'head', 'type', and 'ndim'. Plus, you'll get to know the 'dir' command to access Python objects' directory of methods and properties.

In this lesson of the Python in Excel course, you're going to learn how to turn off the automatic workbook update every time you run a cell in Microsoft Excel. This way, you can use Excel's built-in calculation options (automatic, partial, manual) to make your workflow more efficient.

In this lesson of the Python in Excel course, you're gonna learn how to use the 'describe' and 'info' methods to really dig into the data you've got. This way, you can spot the main features and see if you need to clean up the data before you start making your cool visualizations in Microsoft Excel.

In this lesson of the Python in Excel course, I'm gonna show you how to clean up your data so you don't have any pesky null values messing with your data analysis. There are three ways to go about it, and we're gonna start by dropping columns using Pandas' 'drop' method. We'll check out different ways to use this method, using the 'columns' and 'axis' attributes, and also whether or not to reassign the dataframe value in Microsoft Excel.

In this lesson of the Python in Excel course, I'm gonna show you how to clean up your data so you don't have any null values messing up your data analysis. There are three ways to go about it, and we're gonna dive into how to remove rows using the 'drop' and 'dropna' methods from pandas. We'll check out different ways to use these methods, like using the 'inplace' and 'subset' attributes, and whether or not to reassign the value of the dataframe in Microsoft Excel.

In this lesson of the Python in Excel course, I'm gonna show you how to clean up your data to avoid null values that could mess up your data analysis in Microsoft Excel. There are three ways to tackle this, and today we're gonna look at filling in those empty cells with new values using the 'fillna' method. We'll explore different criteria for filling in those blanks, like using zero or calculated values like the mean, median, or mode. You'll also get to know the 'method' argument in 'fillna' that can be filled with 'ffill' or 'bfill'

In this lesson of the Python in Excel course, you'll get to know Seaborn, a powerful library built on top of matplotlib and Python for creating Python charts, which we'll learn how to use in Microsoft Excel

In this lesson of the Python in Excel course, you will learn how to create a Jointplot type graph from seaborn within Microsoft Excel using Python.

In this Python in Excel lesson, you will learn to explore the Seaborn documentation to understand the parameters of the Jointplot (such as Data, Hue, Kind, Space, Dropna, etc.).

In this lesson of the Python in Excel course, you will learn how to explore the Seaborn documentation to be able to identify how to use any of the charts and resources it offers, and even how to configure them in detail. You will also learn to use the 'help' keyword in Python to obtain contextual help on any Python element without leaving Microsoft Excel.

In this lesson of the Python in Excel course, you will get to know the Formula Editor (Excel Labs) of Microsoft Excel, which is a side editor where you can write all your code in cells, Jupyter Notebook style. You will learn all the options for working with Excel Labs for Python in Excel.

In this lesson of the Python in Excel course you are going to learn about all the possible error messages you may receive while writing Python code in Microsoft Excel, what they mean and how to handle them.