• Data Cleaning and Preprocessing
  • Indexing and Slicing
  • Filtering and Selection
  • Sorting and Ranking
  • Aggregation and Grouping

How to Suppress Scientific Notation in Pandas

Scientific notation is a way of expressing numbers using exponents, which can be useful for very large or very small numbers, but can also make data difficult to read and interpret. Fortunately, Pandas provides a way to suppress scientific notation and display numbers in standard decimal format.

Here are some ways to suppress scientific notation in Pandas: (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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