10 Must-Know Pandas Functions For Data Analysis | Data Analytics With Pandas | Pandas Projects

[@benoniokaikoi7878]

You are an excellent teacher!

[@siddamsettigangadhararao9620]

Such a fantastic lecture, that much easy explanation 👌

[@ahammadali4440]

Great content. Thank you very much

[@DataThinkers]

Glad you liked it!

[@akshrags-mindmaze3407]

You are explaining the concepts in the easiest way....I was struggling with pivot table ...Other channels are making it complicated , but you explained it very easily, thanks.... Is it important to learn the Grouper function in Pivot Table??

[@ahammadali4440]

Could you please make a second part to this pandas function video. This one was amazing. Much appreciated.

[@DataThinkers]

sure. Thanks

[@shiltonshilton5898]

Very very good, we wait more from you, and thanks for this effort, We need also more different projects in EDA and Machine Learning like that find on your channel thanks for you again.

[@DataThinkers]

Thanks, keep watching.

[@shakilahammed1887]

Thanks

[@sanjeevvishwakarma2787]

I just want to say WOW, YOU are fabulous. I learn a lot from your contents. thanks for making such a valuable content. if possible make a video on how to prepare basic portfolio for data analyst students

[@DataThinkers]

Sure, thanks 👍

[@stinkeyboy3302]

namaste kebab teacher🙏

[@jalego800]

I learn lots of Pandas from your turtorials, they're really cool & helpful to me. But I wonder what's the difference between using where() & query() with using a filter? Wouldn't it be more simple to just using a filter? Thanks!

[@DataThinkers]

The main difference between where() and query() is that where() is a method for filtering data based on a condition, while query() is a method for filtering data based on a string expression. Another difference is that where() returns a copy of the original DataFrame or Series, while query() returns a view of the original DataFrame or Series. This means that if you modify the filtered data using where(), it will not affect the original data. On the other hand, if you modify the filtered data using query(), it will modify the original data as well. In general, if you need to filter data based on a simple condition, you should use where(). If you need to filter data based on a more complex expression, you should use query(). However, you should always consider the performance and memory implications of using these methods, especially for large datasets.

[@jalego800]

@@DataThinkers Thank you sir, appreciate your help!

[@nhatquangphan2124]

Can you make more video about deep learning project ? I think it's also important . Thank you

[@DataThinkers]

Yes, after some ML Projects will start. Thanks. Keep watching

[@letsgetjob392]

upload more machine learning projects i was completed all projects in your ML playlists

[@letsgetjob392]

and thanks for giving me projects thank a lot

[@DataThinkers]

Sure

[@akshrags-mindmaze3407]

Can you pls explain qcut()? Kindly reply

[@DataThinkers]

qcut() is a function in pandas that can be used to divide a continuous variable into a set of discrete bins based on the quantiles of the data. Quantiles are the values that divide a dataset into a specified number of equal parts. It's worth noting that cut function uses the bin edges to segment the data, so the size of the bins may not be the same. Unlike the qcut function that uses the quantile value to bin the data, so the bins will have the same number of observations. Hope it clear now.

[@akshrags-mindmaze3407]

@@DataThinkers thanku sir...

[@zaravind4293]

Will you provide data analyst course sir? How can I contact to you sir?

[@DataThinkers]

Send email to me

[@zaravind4293]

@@DataThinkers Can you please share your mail id bro

[@DataThinkers]

[e-mail]

[@SayanBanerjee-b9j]

wonderfull class though but please avoid using 'let me' all the time