What is a Pandas Data frame?

A data frame in pandas is a two-dimensional tabular data structure with labelled axes known as rows and columns. Some of the properties of a data frame are:-

• It can be heterogeneous means columns can have any data type.
• It can be modified into n number of rows and columns (more rows/columns can be added)
• Every data frame has axes defined i.e. rows and columns

Pandas– Pandas is an open-source Python library used widely for performing operations on labelled/tabular data or time series in the data science field. It is fast and efficient for manipulating and analyzing data which helps in increasing productivity while performing data-related tasks.

The Problem– Sometimes we have a data frame where the data is in the form of a string entry in one or more columns and we want to separate that data into rows.

Sometimes when working with data, one may encounter a situation where the string entries present in the data frame need to be split into different rows. This can be a challenging task especially when the data is large and complex. Still, a Python library known as pandas provides various functions using which this task can be accomplished easily and efficiently. So in this article, we’ll be looking into how to convert dataframe entries in string format to separate rows using methods available in pandas i.e. split and explode.