After a lot of search, I finally found this tutorial which shows how to get data from an API and then convert the json into a dataframe. This is pure gold. Thank you
@@stratascratch there are tutorial on how to use API and then different tutorials on converting json to data frame. So far haven’t found a tutorial showing everything end to end.😀
Hi Nate, thank you for this great video! Just a quick tip, if any wants to grab the video data for multiple channel IDs at once you can directly use this method (from UA-cam API doc): request = youtube.channels().list( part='snippet,contentDetails,statistics', id=','.join(channel_ids)) response = request.execute() where channel_ids is a list of channel ids (e.g ['id_1', 'id_2', 'id_3''] and youtube = build('youtube', 'v3', developerKey=api_key)
The best part is how you show in a easy way how to do the whole process and then you clean up the code according to good practices. This was really good, thank you!
Hey Nate, your videos are just too good. I love how your channel is so dedicated towards real word data science. By the way I noticed that you started a video series, "For your Data Science Project" and I really want you to continue making videos for this particular series because there's literally no one on UA-cam with such guidance on DS projects and I have been looking for one since a very long time because I have my placements just after 12 months and I really want to make a full stack data science project. Thank you.
I cannot comprehend right words to express how great this video is and all the content that you create. For all those who dream, plan or wish to make great career in data science you are simply an angel. The most important part which I want to request is a complete playlist of all the components that you mentioned in the : "The one and only one Data Science Project you need". This video covers the data collection part through API...and if other components are covered and all together that playlist would become the gold mine for aspirants. I hope you get time from your busy schedule to consider my humble request... Thanks a lot for all your videos which keep enlightening the Data Science aspirants.🙏
Definitely will create this playlist or at least write an article that will provide you with resources for each part of this project journey. Thanks for the suggest. It's a great idea.
Next highly expected topic can be .. setting up cloud to store the data. We can have a playlist of videos on topics Nate mentioned in the end to end data science project 😊😊
I have been struggling to learn data science from multiple sources and there are hell lot of content.. After scavenging through the dirt pile, garbage of useless information. I can finally say that I have found the most valuable resource available on the internet ! Thank you Nate ! I can finally see light at the end of the tunnel. Love from Delhi, India
This is brilliant. I took way too much time searching and googling and watching hours long videos to find pretty much everything I need in a clear crisp straight forward 30min video. Minus a tiny bit of API beginner information and knowing the basics of Python, this was perfect. Well done. I imagine the next video will be everything I need and nothing that I don’t to take the next step of processing/analyzing the data. I am hitting play on that……. Now!
Thanks for the video Nate. Update : One might get an error in the dislike count part. "The statistics.dislikeCount property was made private as of December 13, 2021. This means that the property is included in an API response only if the API request was authenticated by the video owner. See the revision history for more information."
I really wanna thank you so much cause those are the real skills that we need as entry-level data scientist, i'm an artificial intelligence student and everything they are teaching us is a pure academic which will not cover the practical side.
Hey there! Just a quick tip for anyone trying out the code: make sure you're using a version of pandas earlier than 2.0. Otherwise, you might need to use a different method instead of .append, or consider adding the data to a Python list first and then converting it to a pandas dataframe. Hope this helps! 😊
This is probably the best video i watched so far on use of api in data science cause everywhere else the videos are so long and i could not understand a lot of those tutorials. Thank you so much for this video content.
Now this is real-world, practical knowledge. After watching your video on the one and only data science project you'll ever need, I knew I had found something amazing. After watching this one, I was sold. Just subscribed. Keep these gems coming!
Thank you so much for the detailed breakdown and clear explanations of your code logic! As someone new to Python, I understood each concept but was struggling to piece it all together. This video was incredibly helpful, and you've earned a like and a new subscriber. I'd really appreciate it if you could cover the different types of API authorizations in more detail. A video explaining the requests module, especially how to work with GET, POST, PUT, etc., and their parameters would be great. Also, some guidance on using virtual environments would be very helpful!
Ever since I started my data science learning journey,this might be the most valuable video I have come across,thanks a lot mate,this is extremely helpful.
@@stratascratch now that we have collected the data how are we going to apply ml to this specific task(yt api) My Guess is we need little more info to predict something with good accuracy these are the things I thought for this data: I think we can cluster the video with less views or likes or something like that, one more thing I can think of is predicting views or likes with the help of regression models I cant think of anything else can u please tell me something else
Covered all the basic and important points is a well structured manner to make it simple enough to follow and understand. You have great teaching skills! Thank you for spreading your knowledge.
amazing tutorial. Thank you for your well organized video, your voice and everything you talk about are absolutely clear and help me easily to follow. Please keep your great works
This is definitely the best youtube API video I've been able to find. Thank you so much. I actually went through two other videos before this and this one was the clearest that actually moved into a full pandas dataframe. Thanks!
@@elhipster1 Thanks for noticing how I do it. I always work in this way where I will write code to make sure the function is there. Once the entire script is finished and it's able to function, I'll go back and refactor everything and try to automate things to make my life easier the 2nd time around. It's a good practice for your self. And if you work on a team, you can even share the code with your team so they can use it for their purposes.
This is great, thanks for providing. Sometimes, the apikey is in the header, so it has to be passed that way. I used this to pull the data in from the API I'm presently working with (ATTOM): url = 'the get url' headers = { 'Accept':'application/json', 'apikey':'your api key', 'accept':'application/json' } response = requests.get(url, headers=headers) response.json()
Interesting video. I was able to create my own api key from UA-cam. But since I have no posted videos, it is difficult to conceptualize your teaching. I wish we could get a generic api key to see data populated in the dataframe.
Yea most definitely. Just use the same principles as outlined in the video. Looks like Spotify has 2 python API wrappers (developer.spotify.com/documentation/web-api/libraries/)
Hello Nate, Nice Video, love it! I have a question here, instead of making a second API call for the stats, can we use fields parameter in the URL of the first API call to get the stats. Pardon me if I am not understanding the fundamentals properly. Thanks
Hi Nate, Thanks for making this video and I really enjoyed and learnt from this video. I have a question, do all big/medium companies/startup make their data public via API?
Hey! Thanks for watching. The next video is coming out in 1-2 weeks to close out the series. Sometimes companies make their data public but they usually won't make internal data like user engagement or financial stats public. But they usually do make whatever data you own or whatever is deemed public, accessible to all. Like Twitter has an API you can use to collect tweets because all the tweets are publicly accessible. Hope that helps.
Excellent Code Descriptions - breaking down the loop elements BEFORE creating the code is excellent. I was inspired by this lesson - to improve my data ingestion capabilities. At risk of redirecting viewers - I started a LI Learning course: Data Ingestion with Python, Miki Tebeka. (requires a subscription to LI).
Thanks again Nate, I appreciate the helpful content on understanding/navigating the API through Python. I know you didn't have time in the video to elaborate, but how can we continue looping through pages via 'pageToken' to extract all of data than just the first page?
Great question. I actually have the code in the github repo. There's a link in the description. I use the 'pageToken' to do this as you mention. Check out the implementation!
@@stratascratchWhen I add the "pageToken" some conflist with response['item'] arises. What could be the reason? ----> 4 df = get_videos(df) in get_videos(df) 6 response = requests.get(url).json() 7 time.sleep(1) ----> 8 for video in response['items']: 9 if video['id']['kind'] == "youtube#video": 10 video_id = video['id']['videoId']
Hi Nate, I love the video, super clear and explains a lot. I am struggling with pagetoken, you said it would be explained later, is there another video I need to watch to get a handle on this? Thanks
An API is specifically created to retrieve data. Companies create APIs to do this task. Webscrapping just pulls from elements on the webpage and often isn't legal to do. I've never really needed to webscrape anything working for a company. I think it's much more valuable to learn how to work with APIs.
After a lot of search, I finally found this tutorial which shows how to get data from an API and then convert the json into a dataframe. This is pure gold. Thank you
You wouldn't have thought it would take so long to find a video that does? =) glad you found this channel.
@@stratascratch there are tutorial on how to use API and then different tutorials on converting json to data frame. So far haven’t found a tutorial showing everything end to end.😀
what is the next step after importing a database??
How about applying read_json method ?
Hi Nate, thank you for this great video! Just a quick tip, if any wants to grab the video data for multiple channel IDs at once you can directly use this method (from UA-cam API doc): request = youtube.channels().list(
part='snippet,contentDetails,statistics',
id=','.join(channel_ids))
response = request.execute()
where channel_ids is a list of channel ids (e.g ['id_1', 'id_2', 'id_3'']
and youtube = build('youtube', 'v3', developerKey=api_key)
what is the next process after importing database ??
Thanks a ton
OMG you're here anyway thank youuu thu vu 🥺
The best part is how you show in a easy way how to do the whole process and then you clean up the code according to good practices. This was really good, thank you!
Hey Nate, your videos are just too good. I love how your channel is so dedicated towards real word data science. By the way I noticed that you started a video series, "For your Data Science Project" and I really want you to continue making videos for this particular series because there's literally no one on UA-cam with such guidance on DS projects and I have been looking for one since a very long time because I have my placements just after 12 months and I really want to make a full stack data science project. Thank you.
I cannot comprehend right words to express how great this video is and all the content that you create.
For all those who dream, plan or wish to make great career in data science you are simply an angel.
The most important part which I want to request is a complete playlist of all the components that you mentioned in the : "The one and only one Data Science Project you need".
This video covers the data collection part through API...and if other components are covered and all together that playlist would become the gold mine for aspirants.
I hope you get time from your busy schedule to consider my humble request...
Thanks a lot for all your videos which keep enlightening the Data Science aspirants.🙏
Definitely will create this playlist or at least write an article that will provide you with resources for each part of this project journey. Thanks for the suggest. It's a great idea.
Next highly expected topic can be .. setting up cloud to store the data. We can have a playlist of videos on topics Nate mentioned in the end to end data science project 😊😊
I thought my video speed was on max, but it wasn't; there is just a lot of information being presented. Very comprehensive. Thank you.
Thank you. We love to share what we know. Glad we have helped you.😀
I have been struggling to learn data science from multiple sources and there are hell lot of content.. After scavenging through the dirt pile, garbage of useless information. I can finally say that I have found the most valuable resource available on the internet !
Thank you Nate ! I can finally see light at the end of the tunnel. Love from Delhi, India
Thank you for your kind words! More to come!
This is brilliant. I took way too much time searching and googling and watching hours long videos to find pretty much everything I need in a clear crisp straight forward 30min video. Minus a tiny bit of API beginner information and knowing the basics of Python, this was perfect. Well done. I imagine the next video will be everything I need and nothing that I don’t to take the next step of processing/analyzing the data. I am hitting play on that……. Now!
Made more api progress today than with days of Internet and ai. Thank you. I love how pragmatic this video is.
Thanks for the video Nate.
Update : One might get an error in the dislike count part. "The statistics.dislikeCount property was made private as of December 13, 2021. This means that the property is included in an API response only if the API request was authenticated by the video owner. See the revision history for more information."
What I love most about your content is how you simplify the building process and then refactoring …. I am hooked.
Amazing video ,finally get the understanding how to extract data from the API ,Thanks man
I appreciate your feedback! Thank you too.
As a beginner, this really helps me understand how to work with JSON files and API calls. Thanks for the great content!
Thanks Nate, this is the next level of simplifying a so called complex issue related to an API
I really wanna thank you so much cause those are the real skills that we need as entry-level data scientist, i'm an artificial intelligence student and everything they are teaching us is a pure academic which will not cover the practical side.
Hey there! Just a quick tip for anyone trying out the code: make sure you're using a version of pandas earlier than 2.0. Otherwise, you might need to use a different method instead of .append, or consider adding the data to a Python list first and then converting it to a pandas dataframe. Hope this helps! 😊
Even if you will use append method, it's strongly adviced do not use append as in his video as it's awful for performance. Don't do it!
This is probably the best video i watched so far on use of api in data science cause everywhere else the videos are so long and i could not understand a lot of those tutorials. Thank you so much for this video content.
I spend couple hours figuring out the url's and the api key, but this is a great help, Thanx a lot!
Now this is real-world, practical knowledge. After watching your video on the one and only data science project you'll ever need, I knew I had found something amazing. After watching this one, I was sold. Just subscribed. Keep these gems coming!
This channel deserves million subscribers and views. Keep it up!
Incredible how concisely this whole topic can be presented. Happy to very soon become a StrataScratch subscriber.
Wow, you're really give a huge knowledge for data science projects for free, big thanks man
Thank you so much for the detailed breakdown and clear explanations of your code logic! As someone new to Python, I understood each concept but was struggling to piece it all together. This video was incredibly helpful, and you've earned a like and a new subscriber. I'd really appreciate it if you could cover the different types of API authorizations in more detail. A video explaining the requests module, especially how to work with GET, POST, PUT, etc., and their parameters would be great. Also, some guidance on using virtual environments would be very helpful!
Ever since I started my data science learning journey,this might be the most valuable video I have come across,thanks a lot mate,this is extremely helpful.
Thanks!
simple, short, and efective.
Keep going bro, amazing content
Thanks so much for watching. Glad people like these python videos!
THIS IS ABSOLUTE BLISS TO WATCH!!! THANKS FOR THE AWESOME CONTENT
Glad you enjoy it!
@@stratascratch now that we have collected the data how are we going to apply ml to this specific task(yt api) My Guess is we need little more info to predict something with good accuracy
these are the things I thought for this data: I think we can cluster the video with less views or likes or something like that, one more thing I can think of is predicting views or likes with the help of regression models I cant think of anything else can u please tell me something else
thanks. this thing took me an entire day to finish.
I'm glad you did the project! It's a good one day project
Best video I have seen on APIs. Thank you so much.
Thank you! If there are other projects you're interested in, let me know!
More videos about this, please. Great information. I loved it!
wow, this is amazing! Thank you so much. It was concise and robust. Learnt a lot from it
You are welcome. Happy that you found our video helpful.
You are doing an amazing job. It is what's required to understand the programming side.
Really appreciate the tutorial, tremendously helpful getting my own api project started.
You are the best! Thank you so much for sharing this valuable information
Thank you. We are happy that we were able to help.
Covered all the basic and important points is a well structured manner to make it simple enough to follow and understand.
You have great teaching skills! Thank you for spreading your knowledge.
good work man, best tutorial of collecting data from api !!!!
Glad you think so!
the amount of knowledge in this one video!!!!!!!!!!
God bless you
6:11 that's basically why data engineers are needed
Thank you so much for your videos, I just recently discovered this channel and it is amazing!
Thank Nate for this very clear video on API. It is a great help for me as I'm studying python API , flask etc. right now.
This video : highly recommended 🍁
I forgot to thank you in April: awesome, thanks!
One of the best videos regarding API call. Subscribed.😇😊
this video-storyboard on point. very clear, explain the scope and summarize. thank you!
Very good and easily understandable educational video! Thanks Nate, for making the tech stuff interesting as well !
Super informative video on working with API's
amazing tutorial. Thank you for your well organized video, your voice and everything you talk about are absolutely clear and help me easily to follow. Please keep your great works
Huge thanks! I really like your video. Systematic and clear in your explanation. hope your channel grows! subscribed!
Thanks for watching! And glad you found it educational!
AMAZING tutorial, thanks for sharing!
This is an amazing session, thank you
Oh my god. Your video is a treasure
This is definitely the best youtube API video I've been able to find. Thank you so much. I actually went through two other videos before this and this one was the clearest that actually moved into a full pandas dataframe. Thanks!
Hey thanks so much for the kind words! I tried my best to clearly explain all the steps and theory. I hope to create more in the future.
I really appreciate how you created the 'for' loops, THEN went back and restructured the code to be more 'fundamentally' sound. bravo!
@@elhipster1 Thanks for noticing how I do it. I always work in this way where I will write code to make sure the function is there. Once the entire script is finished and it's able to function, I'll go back and refactor everything and try to automate things to make my life easier the 2nd time around. It's a good practice for your self. And if you work on a team, you can even share the code with your team so they can use it for their purposes.
You just gained a subscriber Bro 😃
Nice content
This is great, thanks for providing. Sometimes, the apikey is in the header, so it has to be passed that way. I used this to pull the data in from the API I'm presently working with (ATTOM):
url = 'the get url'
headers = {
'Accept':'application/json',
'apikey':'your api key',
'accept':'application/json'
}
response = requests.get(url, headers=headers)
response.json()
Very cool! Thanks for sharing.
Fantastic tutorial, easy to follow and presented in a way that is easy to follow
Good old days, you can see dislike_count for any video. Great tutorial, many thanks!
I love this playlist and look forward to seeing more videos in it.👍
Awesome! Thank you!
love your video! Clear explanation and straight to the point
Thanks a million Nate for such a great content. You are an inspiration
Wow this helped so much! Super straightforward thanks!
Thanks Nate for making this easy!!
Brilliant! Great explanation of the process.
Thanks for your video . You make the things easy . Thanks a ton :)
It was very clear and useful. Thank you so much.
Just Awesome
Wonderful. Hope you find the video helpful.
THANK YOUUU man...woow, love this
Perfect Explanations.
Very useful.
Thank you so much.
Thank you for watching!
this is pure gold!
Great video!!!! very easy to follow through!
Interesting video. I was able to create my own api key from UA-cam. But since I have no posted videos, it is difficult to conceptualize your teaching. I wish we could get a generic api key to see data populated in the dataframe.
FANTASTIC tutorial!! What can possibly top this?
Thanks for this video. was really very helpful.
Good stuff and Thank you Nate for sharing!
Thanks for watching!
Thanks! Really appreciated it
Great tutorial, thanks!
i really like your content a lottt can you make more SQL and Databases vides (More Advanced) please and keep going
That diploma looks very familiar - hello Big Red!
Hello Big Red indeed!
Love this tutorial!!
Awesome!!! TQVM!!
Amazing content !
Your tutorials are cool
I have hit a gold mine...
Can you please upload an end to end data science project which includes ml model working on streaming real time data .... Thankyou
Very helpful! thank you
Can we do same for the Spotify ?
Basically i wanted to see all songs heared in previous 24Hrs
Yea most definitely. Just use the same principles as outlined in the video. Looks like Spotify has 2 python API wrappers (developer.spotify.com/documentation/web-api/libraries/)
good stuff, sir!
Hello Nate, Nice Video, love it! I have a question here, instead of making a second API call for the stats, can we use fields parameter in the URL of the first API call to get the stats. Pardon me if I am not understanding the fundamentals properly. Thanks
Could you have made the dataframe appending more efficient with a loop and index [0]? Instead of writing out all 7 key value pairs.
Too good. Thanks a lot.
but i have problem that captcha is getting in the way of me scraping the website.
Hi Nate, Thanks for making this video and I really enjoyed and learnt from this video. I have a question, do all big/medium companies/startup make their data public via API?
Hey! Thanks for watching. The next video is coming out in 1-2 weeks to close out the series. Sometimes companies make their data public but they usually won't make internal data like user engagement or financial stats public. But they usually do make whatever data you own or whatever is deemed public, accessible to all. Like Twitter has an API you can use to collect tweets because all the tweets are publicly accessible. Hope that helps.
pure learning..
Excellent Code Descriptions - breaking down the loop elements BEFORE creating the code is excellent.
I was inspired by this lesson - to improve my data ingestion capabilities. At risk of redirecting viewers - I started a LI Learning course: Data Ingestion with Python, Miki Tebeka. (requires a subscription to LI).
love that
Thank you!
Well done. Nice video.
Thank you very much!
I love your videos!
Thanks, man! Appreciate it
Please link the video you
are referring to in the Intro
Here is the link to the video: ua-cam.com/video/c4Af2FcgamA/v-deo.html
Thanks again Nate, I appreciate the helpful content on understanding/navigating the API through Python. I know you didn't have time in the video to elaborate, but how can we continue looping through pages via 'pageToken' to extract all of data than just the first page?
Great question. I actually have the code in the github repo. There's a link in the description. I use the 'pageToken' to do this as you mention. Check out the implementation!
@@stratascratch Thanks Nate! Appreciate the help. Currently in interviews and I've gotten far with your content!
@@stratascratchWhen I add the "pageToken" some conflist with response['item'] arises. What could be the reason?
----> 4 df = get_videos(df)
in get_videos(df)
6 response = requests.get(url).json()
7 time.sleep(1)
----> 8 for video in response['items']:
9 if video['id']['kind'] == "youtube#video":
10 video_id = video['id']['videoId']
Hi Nate, I love the video, super clear and explains a lot. I am struggling with pagetoken, you said it would be explained later, is there another video I need to watch to get a handle on this? Thanks
What are the differences between API for collecting data and doing webscrapping?
An API is specifically created to retrieve data. Companies create APIs to do this task. Webscrapping just pulls from elements on the webpage and often isn't legal to do. I've never really needed to webscrape anything working for a company. I think it's much more valuable to learn how to work with APIs.
Good work!!!
thank you so much dude
You're welcome!