I am new to the Great Expectations package. I found this tutorial for connecting to a data source, validating the data and visualising the output as a data doc which is saved as an html. https://docs.greatexpectations.io/docs/tutorials/getting_started/tutorial_setup
However I am not able to run the CLI commands used in the tutorial. Is there a way to generate the data docs seen in the tutorial above from a series of expectation results ran on an in-memory pandas dataframe.
This article goes through how to perform the expectation results on a read-in pandas dataframe, and for each expectation outputs a result dictionary, however it does not explain how to take the results and convert them into a data docs. https://towardsdatascience.com/a-great-python-library-great-expectations-6ac6d6fe822e
Minimal Reproducible Example
Python==3.8.15
Packages:
great-expectations==0.15.41
pandas==1.5.2
import pandas as pd
import great_expectations as gx
# simple dataframe
df = pd.DataFrame({'A': [1, 2, 3, 4, 5],
'B': ['a','b','c','d','e']})
# Turn into GX dataframe
df = gx.from_pandas(df)
df.head()
[enter image description here](https://i.stack.imgur.com/5IC9R.png)
gx_result = df.expect_column_to_exist("A")
print(gx_result)
[enter image description here](https://i.stack.imgur.com/yF3tS.png)
# Code to convert expectation result into data doc
I have also found this piece of documentation that refers to creating a data doc, but am unsure how to connect it with the code above. https://docs.greatexpectations.io/docs/terms/data_docs/
Thanks in advance