Convert columns from non-date to date datatypes — In the last tutorial, we looked at the various approaches to read the data files containing the date-time variables. In this tutorial, we will discuss how to handle columns of an existing dataframe that contains date-time data but are still read by Python as an object datatype. Assumption and Recommendation Being hands-on is…

Reading files containing the dates column. — The topic discussed here is a challenge that every aspiring data scientist/ analyst stumbles upon at the start of their data science journey. The challenge with this problem is that you will continue to encounter it in some scenario or the other, and every time you do that, you will…

A common data wrangling challenge and a one-step solution. — During the data preparation stage of an analytics project, a common challenge is to have a list of values in a table’s column. Typically, in a scenario like this, an analyst would like to split it into multiple records. A visual representation of this case is as below:

Converting your data from long-form to wide-form — In the last tutorial, we demonstrated the Pandas melt function to reshape the wide-data form into the long-form. This tutorial will focus on the opposite process. To bring everyone on the same page, presenting a visual of the problem we are trying to solve:

Converting your data from wide-form to long-form — One of the data wrangling scenarios we commonly encounter during the pre-processing stage of an analytics project is to reshape the data. Most of our colleagues starting their data science journey struggle to convert columns into rows and vice versa. …

Using If-Else conditions within loops — Most of us have used the if-else conditional blocks in one or the other programming language. Python goes a step ahead and supports the use of the else conditional block in looping structures too. …

Explaining the working of regular expressions in Python — When writing regular expressions (regex) in Python language, we always start with the letter r. In this tutorial, we will understand the reason behind using it by answering the following questions: What are the escape sequences? How Python interpreter interprets escape sequences with or without the letter r? How regular…

Making Python Easy — When working on a data science project, we spend more than 70% of our time adjusting data to our needs. While munging data, we encounter many scenarios for which ready-made solutions are not available in standard libraries like pandas. One such scenario is when we have to create multiple dataframes…

Beginner’s Guide To Anaconda — A good handle on Package and Environment management ensures that we continue to avail the benefits of the latest package functionalities while ensuring that projects running on older package releases do not break down. This tutorial is a beginner’s guide to learn both package and environment management using Conda that…