Thank you Brilliant for sponsoring this video! Check out brilliant.org/KeithGalli/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription. Hope you all enjoyed this video :). I'm working on a bunch of new content right now so be on the lookout for another video or two in the next couple of weeks. If you have any questions about the topics covered in this or have a request for a future video, let me know here in the comments!!
Hi @KeithGalli. I’ve got two questions to ask you. I have watched lots of your videos that I like, and learned a lot. My question is do you think that the certificate that Datacamp provides for data science is worth to earn, and would it help me to find a data science job? And, what best place, you recommend, in online to get certificate for data science that would help me to find a data science job? Thank you.
At 37:48 I work for Amazon's RPA team, trying to make a career in data science. Last month I was appearing for an IJP and got the same question in SQL coding round. Thanks for making this Keith. Keep them coming.
Hey Hardik, can you tell me why exactly you are trying to make a career in Data Science? Is it because RPA doesn't have a good future in the industry or it is because you personally prefer the Data Science field. I am asking this question as I am also starting as a member of EXL's RPA team.
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')
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!
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.
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.
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.
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']]
That first one and others are SQL problems converted to pandas. I suppose that's a decent way to get basic pd questions. (28:48) 17:20 I know it's more a reference to the stock market terms, but I can't stop thinking of Fallout: New Vegas. 1:11:00 If you have the locations that's just a simple matter of putting it on a map and seeing where it clusters the most. 1:28:00 Context, context, context. Was that the only reduction?
I think that for the probability of getting a sister given that they have 2 children is 0.75 Sample space Sister,brother Brother,sister Sister,sister Brother,brother 3/4 And for 3 children you need to account for the chance that the three children are girls so it will be 7/8
Hey Keith, dunno if this changed from 2 years ago when you posted this video, but currently the 'Check Solution' button is only available for Premium Users :/ Still, seeing how you go about solving the problems is great to get in the right mindset!
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.
My apologies! I have a video that I'm finalizing the editing for. It should be out in the next 3-4 days and then I'm going to try to be more consistent!!
Thank you Brilliant for sponsoring this video! Check out brilliant.org/KeithGalli/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription.
Hope you all enjoyed this video :). I'm working on a bunch of new content right now so be on the lookout for another video or two in the next couple of weeks. If you have any questions about the topics covered in this or have a request for a future video, let me know here in the comments!!
Hi @KeithGalli.
I’ve got two questions to ask you. I have watched lots of your videos that I like, and learned a lot.
My question is do you think that the certificate that Datacamp provides for data science is worth to earn, and would it help me to find a data science job?
And, what best place, you recommend, in online to get certificate for data science that would help me to find a data science job?
Thank you.
At 37:48
I work for Amazon's RPA team, trying to make a career in data science. Last month I was appearing for an IJP and got the same question in SQL coding round.
Thanks for making this Keith. Keep them coming.
Dang that's too funny. My hope is that this video will help people in similar situations to yours moving forward. Thanks for watching!
Hey Hardik, can you tell me why exactly you are trying to make a career in Data Science? Is it because RPA doesn't have a good future in the industry or it is because you personally prefer the Data Science field. I am asking this question as I am also starting as a member of EXL's RPA team.
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')
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!
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.
good having you back
Good to be back! :)
Glad to see you back mate. I have really learned more from your videos than attending University.
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.
Yay! Another real world problem solving video. Thanks Keith. Love your content as always.
Glad to hear it, I appreciate your support!! :)
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)))
Great video btw!
Glad you're back bro!
thanks brother!!
Hi Keith,
You have been a great resource to learn Python and Data science-related skills.
Thank you!
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.
makes it easy to understand
watching your vid on a friday night and these are the best years of my young life
Glad you're back bro ;) love this types of vids. Love from Portugal
Thank you for coming back🤗
Happy to be back!!
really love the style and format of vid, just subbed
Glad you liked it man! Thanks for the sub
Thanks for the video. It is great to see your thinking process even though you are not an expert in pandas.
Thank you so much for these data science courses!
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']]
Oh cool, I didn't know that! Thanks for sharing :). Nice solution 🤠.
Hi Keith , Thank you so much for these videos, could you make more videos about power PI or Tableau, really really appreciate it .
Thanks for the video! Would love to see your approach to more non-coding questions specifically :)
You are gem ❤️ the way you explain concepts are at next level 🔥🔥
Great video, Keith!
That first one and others are SQL problems converted to pandas. I suppose that's a decent way to get basic pd questions. (28:48)
17:20 I know it's more a reference to the stock market terms, but I can't stop thinking of Fallout: New Vegas.
1:11:00 If you have the locations that's just a simple matter of putting it on a map and seeing where it clusters the most.
1:28:00 Context, context, context. Was that the only reduction?
These stratascratch tasks could be solved in sql. The site provides this option.
amazing! we want more of this stuff 👌
Appreciate it! More coming soon :)
Yeeeeeeeeyyy!!!! i love your enthusiastic cry of success :D 26:31
Great video, please do more like that. Watching you for a long time
Very helpful. Thank you Keith.
long time no see keith, welcome back 😀😀
Thank you Keith, you're amazingg, keep it up!!!
Really helpful video!
Brilliant video! very helpfil
Great work man!! you're always doing the best.🔥🔥🔥
Thank you for the support as always!!
yes please make more videos like this
The problem lays in your use of round function you supposed to wrap the equation with round and then select the decimals 2
Thank you for this video!👍
great video, please make more video like this
That was great. Bravo and all of your videos are awesome 🌺👌💞🤩💪
It is very great. Thank You!
Welcome back Keith 💃🏻💃🏻
Is dsa important for data scientists too keith
you are helping a high schooler out by being back
More videos coming soon :)
great video! thank you!
Thanks Keith
I think that for the probability of getting a sister given that they have 2 children is 0.75
Sample space
Sister,brother
Brother,sister
Sister,sister
Brother,brother
3/4
And for 3 children you need to account for the chance that the three children are girls so it will be 7/8
Bravo 👏 Lit 🌠 Impressive 👌 ❤ Gratitude 🥳 for your satisfactory Work 💪🚀💯💪
Could you actually google for help during a DS coding interview nowadays?
Great video Keith. I just got curious how you comment a block of code?
Highlight and ctrl+/
Hey ,Keith ..Can we access library during the solving at real time exam?
Hey Keith, dunno if this changed from 2 years ago when you posted this video, but currently the 'Check Solution' button is only available for Premium Users :/
Still, seeing how you go about solving the problems is great to get in the right mindset!
Hey!
Does anyone knows more of the data analysis pay after placement programs accepting applications all over the globe?
how can i download or copy the raw dataset for each part ?
excellent, thanks.
You're welcome :)
Replace yes with 1 and no with zero and sum them
LifeHack: if you are short of money, but want to use a service, use vpn of relatively poor country. Result will be interesting.
did you ever use it? and on which website?
TY :)
Thanks so much for the video, learn a lot from you. And you are super cute 😍
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.
super
@KeithGalli I don't know why you look like Elon Musk must to me 🤣🤣
Haha I'll take it xD
Hi, I'm Jiemeu and I love your channel. I hope to discuss business cooperation with you.....
Noice!
Probably not a good use of your time to watch this guy struggle with coding questions for over an hour
you disappeared again 😢
My apologies! I have a video that I'm finalizing the editing for. It should be out in the next 3-4 days and then I'm going to try to be more consistent!!
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()
Simple Solution for #5
(sf_transactions
.assign(year_month = lambda df_: df_.created_at.dt.strftime('%Y-%m'))
.groupby('year_month', as_index=False)
.agg(revenue = ('value', 'sum'))
.assign(revenue_diff_pct = lambda df_: df_.revenue.sub(df_.revenue.shift(1)).div(df_.revenue.shift(1)).mul(100))
.loc[:, ['year_month', 'revenue_diff_pct']]
)