Syntax pandas.pivot(data, index=None, columns=None, values=None) Return Value: The return value for the pivot() function is a reshaped DataFrame organized by index/column values. Background Direct quote from the Pandas Documentation website: This function does not support data aggregation. If there are multiple values, they will result in a Multi-Index in the columns. This article delves into … Read more
Syntax pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name=’value’, col_level=None, ignore_index=True) Return Value The return value for the melt() function is an unpivoted DataFrame. Background Direct quote from the Pandas Documentation website: “This function massages a DataFrame into a format where one or more columns are identifier variables (id_vars). While all other columns are considered measured variables (value_vars), … Read more
In this tutorial, we will learn how to transform a JSON object into a Pandas data frame and the other way around. For these approaches, we will have a look at the Pandas functions read_json() and to_json(). Working with JSON objects in Pandas is a very essential skill because we often find data stored in … Read more
In this tutorial, we will learn how to read in HTML tables using the read_html() function and how to turn these tables into Pandas data frames to analyze them. Furthermore, we will see how to render Pandas data frames as HTML tables applying the to_html() function. As you go through the article, you can also … Read more
Part 2 of Working with Excel centers around accessing data from the Active Worksheet. This skill is one of the must-haves if you are interested in pursuing a career as a Data Scientist. Background After completing Part 1 of this series, you should be comfortable using Python to: create an Excel file, import a library, … Read more
In this article, we explore 10 Python libraries, platforms, tools, and frameworks that are useful for e-commerce. Criteria for the list included their relevance to e-commerce, popularity, the level of maintenance that is given to the code base, and their usefulness. We searched far and wide and narrowed down our search to the following: Saleor … Read more
The data we use in Pandas for real-world projects often comes from outside sources. One popular and repeatedly used source is Excel. In this tutorial, we will learn how to read files from Excel, how to modify these files, and how to write them to Excel. We will use several Pandas functions for these approaches. … Read more
To provide a solid understanding of data manipulation with Excel, the Finxter Academy has created a 6-part series to take the user from beginner to advanced. This article assumes that Microsoft Excel is available on the computer. Quick Intro In most cases, working with large amounts of data requires some manipulation to make it more … Read more
In this tutorial, we are covering the Pandas functions loc() and iloc() which are used for data selection operations on dataframes. By using the loc() function, we access a group of rows and/or columns based on their respective labels, whereas the iloc() function is an integer-location-based way to access these groups. Getting values with the … Read more
A box plot is a method used in statistics to graphically show a group, or groups, of numerical data with their quartiles identified. A box plot is often also called a box-and-whisker plot, as the plot may have lines extending from the box to show data outside the upper and lower quartiles. In this article, … Read more
The Pandas DataFrame filter() Method In this tutorial, we will have a look at the Pandas filter() method. We will see what this function does and how we can apply it to our dataframes. As the name suggests, the filter() method filters our dataframe. To be more specific, the method subsets the rows or columns … Read more
In this tutorial, we will see what the Pandas groupby() method is and how we can use it on our datasets. Described in one sentence, the groupby() method is used to group our data and execute a function on the determined groups. It is especially useful to group a large amount of data and to … Read more