This is the last video on learning python for data analytics and data science! Next videos will be ML models! How did you find the series? Please let me know below!
Again, thanks for the nice video. For the bar labels, how do you know that for the index value = 0 needs to be passed in the container object i.e., ax.containers[0]. I have gone through the documentation but there is no elaborated explanation with examples
Secondly, when using the group by based on carboy and fueltype with a mean price value, the graphical output is not in according with the raw output in terms of sorting of the attribute values, as an example hardtop is in the second and third place as compared to what's appearing in the barplot
![Machine Learning Tutorial for Beginners - Linear Regression Example in Python [Part 1]](http://i.ytimg.com/vi/Q0Q4x58h_BA/mqdefault.jpg)
![Machine Learning Tutorial for Beginners – Linear Regression Example in Python [Part 1]](/img/tr.png)
This is the last video on learning python for data analytics and data science! Next videos will be ML models! How did you find the series? Please let me know below!
Great content Yiannis! Thanks
Thanks Tom!
Excellent videos!! very helpful and clear!!I would recommend to make a video trying to predict crypto prices using an ML model (e.g. RNN) in Python.
I cannot begin to tell you just how helpful these videos have been as a data science student. Looking forward to more great content, thanks a lot.
Again, thanks for the nice video. For the bar labels, how do you know that for the index value = 0 needs to be passed in the container object i.e., ax.containers[0]. I have gone through the documentation but there is no elaborated explanation with examples
Secondly, when using the group by based on carboy and fueltype with a mean price value, the graphical output is not in according with the raw output in terms of sorting of the attribute values, as an example hardtop is in the second and third place as compared to what's appearing in the barplot