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May 2, 2022 - Python
dataframe
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We now have native ODBC support upstream. This has to be exposed in polars similarly to existing IO readers and writers.
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Apr 17, 2022 - Java
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.
to_dict() equivalent
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.
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)
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:


pline = pdp.PdPipeline([
pdp.FreqDrop(2, 'a', prec=pdp.cond.HasAllColumns(['x']))
])
pline.apply(
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Jan 6, 2019 - Python
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Jun 4, 2021 - Python
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Apr 26, 2022 - Python
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Apr 23, 2022 - Clojure
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