dataframe

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Description
Please provide a clear and concise description of the problem. This should contain all the steps nee

We now have native ODBC support upstream. This has to be exposed in polars similarly to existing IO readers and writers.

Is your feature request related to a problem? Please describe.
Our Python docstrings have various style violations when compared against standards like pep257. Not only does this impact readability (which may be subjective), it also reduces the effectiveness of tools like Sphinx or numpydoc that rely on specific formatting in order to parse docstrings.

I would like to convert a DataFrame to a JSON object the same way that Pandas does with to_dict().

toJSON() treats rows as elements in an array, and ignores the index labels. But to_dict() uses the index as keys.

Here is an example of what I have in mind:

function to_dict(df) {
    const rows = df.toJSON();
    const entries = df.index.map((e, i) => ({ [e]: rows[i] }));
  

For example, the data is (3.8,4.5,4.6,4.7,4.9)
while I'm using tech.tablesaw.aggregate.AggregateFunctions.percentile function, the 90th percentile is 4.9, however, if the percentile function supports linear interpolation, the 90th percentile should be 4.82, which is adopted by most other programming languages.

Hi,

So first off this problem persists across multiple plugins and code. I love the pandas_ta library thus was hoping we could find a solution here.

First off here is the difference in values:

![image](https://user-images.githubusercontent.com/104263942/164912536-3a72976a-c630-

Is your feature request related to a problem? Please describe.
Implements classification_report for classification metrics.(https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html)

A section in CONTRIBUTING.md for Code Formatting would be useful for new developers to understand patterns, standards, and also prevent unnecessary commits with linter errors.

Describe the solution you'd like
A short section in CONTRIBUTING.md explaining to new devs how to format their code from the cli and as part of pre-commit

Hi ,

I am using some basic functions from pyjanitor such as - clean_names() , collapse_levels() in one of my code which I want to productionise.
And there are limitations on the size of the production code base.
Currently ,if I just look at the requirements.txt for just "pyjanitor" , its huge .
I don't think I require all the dependencies in my code.
How can I remove the unnecessary ones ?

For pipeline stages provided by the pdpipe.basic_stages, supplying conditions to the prec and post keyword arguments may not return the correct error messages.

Example Code

import pandas as pd; import pdpipe as pdp;
df = pd.DataFrame([[1,4],[4,5],[1,11]], [1,2,3], ['a','b'])
pline = pdp.PdPipeline([
  pdp.FreqDrop(2, 'a', prec=pdp.cond.HasAllColumns(['x']))
])
pline.apply(