Published in Python in Plain English·Feb 16Member-onlyData Scientist Interview Coding QuestionA step-by-step guide to coding test EDA — MOTIVATION Currently, it is a norm for companies to implement coding tests as their job initial assessment. The long interview process and timed coding test can be discouraging. …Coding5 min readCoding5 min read
Published in Python in Plain English·Jun 6, 2021Member-onlyHow to convert google colab jupyter notebook (.ipynb) to HTMLOften, we need to share our code explanations and figures written in a Google colab Jupyter notebook (.py or .ipynb files) with our friends/colleagues/bosses. The simple way is to save them as PDF files. However, PDF files are unable to load large figures or the markdown explanations. An alternative way…Python2 min readPython2 min read
Published in Towards Data Science·Sep 13, 2020Exploratory Data Analysis on Heart Disease UCI data set**| A complete step-by-step exploratory data analysis with simple explanation. — Motivation Exploratory Data Analysis (EDA) is a pre-processing step to understand the data. There are numerous methods and steps in performing EDA, however, most of them are specific, focusing on either visualization or distribution, and are incomplete. Therefore, here, I will walk-through step-by-step to understand, explore, and extract the information from…Exploratory Data Analysis8 min readExploratory Data Analysis8 min read
Published in Python in Plain English·Sep 2, 2020Member-onlyHow to use Pandas-Profiling on Google ColabAutomated exploratory data analysis using Pandas Profiling in Jupyter on Google Colab — Recently, pandas have come up with an amazing open-source library called pandas-profiling. Generally, EDA starts by df.describe(), df.info() and etc which to be done separately. Pandas_profiling extends the general data frame report using a single line of code: df.profile_report() which interactively describes the statistics, you can read it more here.Google Colab3 min readGoogle Colab3 min read
