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pandas
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Describe the bug
When downloading this subset as of 3-28-2022 you will encounter a split size error after the dataset is extracted. The extracted dataset has roughly ~6m rows while the split expects <1m.
Upon digging a little deeper, I downloaded the raw files from https://s3.amazonaws.com/amazon-reviews-pds/tsv/amazon_reviews_us_PC_v1_00.tsv.gz
and extracted them. A line count via `wc -
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- 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
I naively tried to do dd.merge(a, b, on="column_with_ten_values")
, where a
and b
were both large DataFrames with thousands of partitions each.
Eventually the compute failed with:
[File /opt/conda/envs/coiled/lib/python3.9/site-packages/dask/dataframe/multi.py:275, in merge_chunk()
File /opt/conda/envs/coiled/lib/python3.9/site-packages/pandas/core/frame.py:9329, i
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Is your feature request related to a problem? Please describe.
Based on discussion in rapidsai/cudf#10200 (comment) there are a number of improvements we should make to the exceptions libcudf throws when a CUDA error occurs.
Describe the solution you'd like
- Add a
cudaError_t
member to [cudf::cuda_error
](https://github.com/rapidsai/cud
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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.
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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] }));
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Pandas version checks
main
hereLocation of the documentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.loc.html
Documentation problem
The Original documentation is as follows.
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