pandas

Currently, we use flake8-rst for running flake8 in code snippets in rst files:

https://github.com/pandas-dev/pandas/blob/2e56a838cf5ed3058df16c11e5ebae862520bab7/.pre-commit-config.yaml#L95-L102

However, flake8-rst isn't maintained, and is currently run in its own environment with a different flake8 version because of incompatibilities with flake8 v4

Task here is:

• search around to see

Describe the bug

Streaming Datasets can't be pickled, so any interaction between them and multiprocessing results in a crash.

Steps to reproduce the bug

import transformers
from transformers import Trainer, AutoModelForCausalLM, TrainingArguments
import datasets

ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True).with_format("

• Base README.md
• Quizzes
• Introduction base README
  • Defining Data Science README
  • Defining Data Science assignment
  • Ethics README
  • Ethics assignment
  • Defining Data README
  • Defining Data assignment
  • Stats and Probability README
  • Stats and Probability assignment
• Working with Data base README
  • Rel

We're trying to introduce Parquet into our team, and the largest blocker that we've seen is the dreaded "schemas are inconsistent" error message:

RuntimeError: Schemas are inconsistent, try using to_parquet(..., schema="infer"), or pass an explicit pyarrow schema. Such as to_parquet(..., schema={"column1": pa.string()})

This error message is super unhelpful: surely Dask knows what th

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.

Reading currencies, alphavantage returns a greeting note ("welcome") and this note raises an error in alphavantage.py line 363.

            elif "Note" in json_response and self.treat_info_as_error:
                raise ValueError(json_response["Note"])

For this reason, alphavantage does not work in home assistant.

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] }));