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…)

Continue ReadingHow to remove nan values in Pandas