Learn how to read a CSV file and create a Pandas DataFrame
As a Data Analyst or Data Scientist, you will frequently have to combine and analyse data from various data sources. A data type I commonly get requested to analyse is CSV files. CSV files are popular within the corporate world as they can handle powerful calculations, are easy to use and are often the output type for corporate systems. Today we will demonstrate how to use Python and Pandas to open and read a CSV file on your local machine.
You can install Panda via pip from PyPI. If this is your first time installing Python packages, please refer to Pandas Series & DataFrame Explained or Python Pandas Iterating a DataFrame. Both of these articles will provide you with the installation instructions and background knowledge for today’s article.
The most challenging part for me when learning Pandas was the number of tutorials there was for Pandas functions such as
.read_csv(). However, the tutorials tended to miss the intricacies you needed when dealing with real-world data. In the beginning, I often found myself having to post questions on StackOverflow to learn how to apply specific parameters. Below we have included all the parameters along with examples for the more conceptually complex.
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