Skimpy a better way to analyze your df than `.describe()`
Another Python and Data post today for you, by me, with the help of what I read on Twitter ... and used. Now it's time to share it with you too!
What is skimpy?
skimpy is a light weight tool that provides summary statistics about variables in data frames within the console. -- Philip Vollet
I tested it just after seeing the tweet. And I could say it's great and I like it! Yes, it's no news that I like data and this library from Python could be used for SEO purposes.
How to install skimpy?
You can:
- go to https://github.com/aeturrell/skimpy
- do a
pip install
- load it thanks to
from skimpy import skim
- test it on your dataframe
skim(df)
These steps are:
1!pip install2from skimpy import skim3skim(df)
Where df
will be your dataframe with you own data. If you want to test it out of the box, there is a test data df that you can create with df = generate_test_data()
What could be the output of skimpy
This is an example I took from one of my data frame from GSC data -- as you will see with clicks and impressions from the screen capture below.
What do we learn with skimpy? More information on your dataframe and I found it more complete than .describe()
from pandas.
Coming from a ... tweet of mine
This is coming from on of my tweet: https://twitter.com/ArthurCa/status/1446481101539717121