How To Clean Data With Python Pandas Pipes

#Python #Pandas #DataScience #Pipes
How To Clean Data With Python Pandas Pipes
In this video we will cover cleaning data in python with pandas pipes functionality.
Using pandas pipes along with reusuable functions we can create a reusuable template for data analytics projects which can cut down on time cleaning data.

Topics covered in this video also include dealing with nulls in python using panadas dropna and fillna functions as we cover droping rows with nulls completely and encoding null cells with averages. We also cover replacing values in datframes and changing types of dataframe columns with Pandas.

The notebook used in this video can we downloaded by going to the following link.

[StefanoComuzzi]

Great video, but the return instruction inside func 2 and func 3 should not be indented inside the for loop, the result is OK only becuse you pipe it with a one element list.

[StefanoVerugi]

nice explanation of pipes, thanks
I particularly appreciate the use of notebook with scripts already in place, many tuts spend most of their time typing which is quite boring sometimes, subscribed

[MadhurDevkota]

one minor things to add....it is not a good practice to use implace (various use df = manipulated data

[ericsamson]

Great video. One point though, you should use method chaining on the pipe functions at the end. Subscribed!

[Adi]

Can we use pipe in with the functions that do not take data frame as input or return data frame as output.

[milanpatel]

I had a NaN thats self-employed. She's now retired. I'll get my coat.