One of the first decisions you need to make when transforming data in Python is what data structures to use. Data structures are the ways of organizing and storing data in memory, such as lists ...

This course will equip you with all the skills you need to clean your data in Python, from learning how to diagnose your data for problems to dealing with missing values and outliers. At the end of ...

Dealing with missing values is a common task in data science that can significantly impact your analysis. In Python, you have multiple strategies at your disposal to handle such data, each with ...

In this GitHub post, I'll share a comprehensive data preprocessing pipeline implemented in Python, which includes handling missing values, outliers, and normalization. Description: This data ...

In order to store key-value pairs in Python, you can use the dictionary data structure. The dictionary functions in a similar fashion to the Python list, in that it is a collection of data.

It is very common to analyze time series data, and the date and time stamp values can come in many different formats. Python supports converting from dates to strings and back. For example ...

Streamlit lets you write web-based Python data applications without HTML ... streamlit.session_state is a key-value store—essentially a dictionary— that persists across runs.