Solving Real-World Data Science Interview Questions! (with Python Pandas)

this took me a week to finish all coding questions, 10000% helped me alot to practice everything i learned in your previous pandas crash crourse. thanks

Your solution for the Probability of Having a Sister question is not correct. We know for sure that the random girl must be from the [1, 2, 3, 4] part of the dataset, which amounts to 0.7. We should divide the probabilities for 1, 2, 3, 4 with 0.7, to get the probabilities that the girl is from each of these families. She theoretically can't be from families with 0 and 5 children. Essentially, you are counting in the possibilities of she being in families 0 and 5, even tough it's impossible. (In practical terms, you are needlessly being blind about the info you already have.) So the correct solution is: 0.25/0.7 x 0 + 0.2/0.7 x 0.5 + 0.15/0.7 x 0.75 + 0.1/0.7 x 0.875 = 0.42857, which is 0.43 when we round it up.

In question #3 Counting Instances in Text you should add filters=re.I to account for capital letters: len(re.findall(r'\bbull\b', text, flags=re.I)))

Is dsa important for data scientists too keith

Brilliant video! very helpfil

I really like your approach in explaining things. I am currently transitioning from pure maths into data science, and I find these videos very helpful!

I really enjoy the real world feel of your videos. Probably now ChatGPT would be a lot faster than searching Stackoverflow or the Pandas docs for those things that one doesn't know by heart.

I solved the Bathrooms/Bedrooms problem with:

cols_of_interest = airbnb_search_details[['city', 'property_type', 'bathrooms', 'bedrooms']]
property_results = cols_of_interest.groupby(['city','property_type']).agg(
avg_bathrooms = ('bathrooms', 'mean'),
avg_bedrooms = ('bedrooms', 'mean')).reset_index()

Hi Keith , Thank you so much for these videos, could you make more videos about power PI or Tableau, really really appreciate it .

Great video, Keith!

Could you actually google for help during a DS coding interview nowadays?

super

Replace yes with 1 and no with zero and sum them

The problem lays in your use of round function you supposed to wrap the equation with round and then select the decimals 2

TY :)

you disappeared again 😢

Thanks so much for the video, learn a lot from you. And you are super cute 😍

Great video Keith. I just got curious how you comment a block of code?

Thank you for this video!👍

You're literally the best tutor I have seen, I myself am a Data Scientist but the amount of data science approaches I learn from you is incredible, I started from your channel and always wait for you to post new video, Hat's off. Love from Pakistan.

Great video, please do more like that. Watching you for a long time

makes it easy to understand
watching your vid on a friday night and these are the best years of my young life

Hi, I'm Jiemeu and I love your channel. I hope to discuss business cooperation with you.....

Hey ,Keith ..Can we access library during the solving at real time exam?

Hey!
Does anyone knows more of the data analysis pay after placement programs accepting applications all over the globe?

Noice!

really love the style and format of vid, just subbed

You are gem ❤️ the way you explain concepts are at next level 🔥🔥

yes please make more videos like this

Thanks for the video! Would love to see your approach to more non-coding questions specifically :)

Great work man!! you're always doing the best.🔥🔥🔥

Thanks for the video. It is great to see your thinking process even though you are not an expert in pandas.

great video, please make more video like this

Here's a one liner chained version I've come up with for coding #6
df = ms_user_dimension.merge(ms_acc_dimension, on = 'acc_id').merge(ms_download_facts
,on ='user_id').pivot_table(index = 'date',columns = 'paying_customer',values = 'downloads',aggfunc ='sum').reset_index().query('no > yes')

That was great. Bravo and all of your videos are awesome 🌺👌💞🤩💪

Hi Keith,

You have been a great resource to learn Python and Data science-related skills.

Thank you!

great video! thank you!

Very helpful. Thank you Keith.

Thank you for all the hard work you put into teaching Data Science. Your videos and others like you, provide more to the community such as myself trying to build a career in data than what University Programs provide. Your playing an important role in the future of Data Science by leading current students along the path to future industry leaders.

how can i download or copy the raw dataset for each part ?

Thank you so much for these data science courses!

Thanks Keith

Welcome back Keith 💃🏻💃🏻

excellent, thanks.

Thank you Keith, you're amazingg, keep it up!!!

Really helpful video!

For the fifth problem, pandas has an in-built percentage difference method (pct_change). The solution could be as follows for example:

sf_transactions['year_and_month'] = sf_transactions.created_at.dt.strftime("%Y-%m")
monthly_revenue = sf_transactions.groupby(["year_and_month"]).sum().reset_index()
monthly_revenue['pct_change'] =(monthly_revenue.value.pct_change()*100).round(2)
monthly_revenue[['year_and_month','pct_change']]