Pandas fundamentals every data scientist needs to know - Part 3

Learn the most important Pandas fundamentals to boost your performance and start coding like a pro in no time!

Pandas can be intimidating at first but it's such a great library with so much potential and so much flexibility. In this series, I will talk about the main working principles of Pandas I have picked up over the years. These will boost your coding performance as they will help you understand how your code works in the background.

In this part, we talk about how to think of the dataset when doing data processing.

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[TechMod-lgec]

I Am Data Science Learner.... Love Your Videos... Awesome Way of Delivering Pandas knowledge

[LuisRomaUSA]

Love your content, and probably by now you have learned this, but "apply functions" are also loops in your data frame, just built-in syntax on pandas but still a loop. To get a non-loop version of the solution you can use numpy as follows:
users['gender_in_binary']= np.where(gender=='male', 1,
(np.where(gender='female', 0, None)))

[TechMod-lgec]

really Amazing Kniwledge for Data Cleaning and preparation

[vijayppatel]

FYI: I am trying to learn D.S and never worked on it.

1. I was expecting None where gender is NOT Male or Female, but it display NaN, Why? (Lambda function)
2. You was truing to set it to Binary Male to 1 and Female to 0, but 1.0 and 0.0 is Not a Binary, then you use fillna it turn into 1 and 0 how?