How to Cast to String in Pandas?

Pandas is a powerful Python library for data analysis. It provides a variety of functions for manipulating and analyzing data, including the ability to cast columns to different data types.

In this article, we will learn how to cast a column in a Pandas DataFrame to a string type. This can be useful for a variety of tasks, such as formatting data for printing or saving, or for performing operations that are only supported on string data types.

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How to subtract dates in Pandas

In Pandas, you can subtract two dates to get the time delta between them. The result will be a Timedelta object, which represents the difference between two dates or times in terms of days, seconds, microseconds, milliseconds, minutes, hours, weeks, or years.

For example, consider the following two dates: (more…)

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How to remove nan values in Pandas

Pandas is a popular Python library for data analysis and manipulation. One of the common tasks that you may encounter when working with Pandas is dealing with missing values, also known as nan values. Nan stands for not a number, and it indicates that the value is undefined or invalid. Nan values can arise from various sources, such as reading data from a file, performing calculations, or applying transformations.

Nan values can cause problems for some operations, such as sorting, aggregating, or plotting. Therefore, you may want to remove them from your data frame or series. There are two main ways to do this: using the dropna() method or using the fillna() method.

The dropna() method removes any rows or columns that contain nan values from your data frame or series. You can specify how to handle the missing values by using the following parameters: (more…)

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How to VLOOKUP in Pandas

In this article, I try to show how to vlookup in Pandas.

The VLOOKUP function in Excel is a popular function that allows you to search for a value in a table and return the corresponding value from another column. The equivalent of a VLOOKUP in Pandas is the merge method, which allows you to join two DataFrames based on a common column.

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