dataframe

vaex.from_arrays(s=['a,b']).s.str.replace(r'(\w+)',r'--\g<1>==',regex=True)

when using capture group in str, it fails, while str_pandas.replace() is correct

Name: vaex
Version: 4.6.0
Summary: Out-of-Core DataFrames to visualize and explore big tabular datasets
Home-page:

Is your feature request related to a problem? Please describe.
Hi,

While porting some code from Pandas to cuDF, I have noticed that cuDF series do not support unstack method.
As an additional request, It would be great if fill_values could be supported in both cudf.DataFrame.unstack and cudf.Series.unstack methods. Thanks!

Describe the solution you'd like
To have that meth

Edited request

Can polars allow mixing string and type selection using col(["x", pl.Int64])

See suggestion here.

Initial request

Any thoughts on an .include() method that is the opposite of .exclude()?

That way these would both work:

df.select(col('x').include(pl.Int64))

df.se

Describe the bug

df.sort_values() failed when input dataframe is empty.

To Reproduce
To help us reproducing this bug, please provide information below:

1. Your Python version
2. The version of Mars you use
3. Versions of crucia

It would be really useful if there was a method that could insert a column into an existing Dataframe between two existing columns. I know about .addColumn, but that seems to place the new column at the end of the Dataframe.

For example:

df.print()

A | B 
======
7 | 5
3 | 6

df.insert({ "afterColumn": "A", "newColumnName": "C", "data": [4,1], inplace: true })
df.print()

Is your feature request related to a problem? Please describe.
My request is a new indicator called Clenow momentum.
Describe the solution you'd like
It measures momentum by getting the exponential regression of log prices and the Coefficient of Exponential Regression depending on the rolling days. It can detect trends in a stock as well as the direction of the stock.

**Addition

Describe the bug

I have a data set created by Apache Spark and I tried to query it from the DataFusion CLI. It failed, saying that a parquet file was corrupt.

 CREATE EXTERNAL TABLE store_sales STORED AS PARQUET LOCATION 'store_sales.dat';
0 rows in set. Query took 0.002 seconds.
❯ select count(*) from store_sales;
Parquet reader thread terminated due to error: ParquetError(Gener

It does not help users view the data when all that is printed on the screen is column names.

Here is pillar output where the number of columns goes into the thousands

Background

This thread is borne out of the discussion from #968 , in an effort to make documentation more beginner-friendly & more understandable.
One of the subtasks mentioned in that thread was to go through the function docstrings and include a minimal working example to each of the public functions in pyjanitor.

Criteria reiterated here for the benefit of discussion:

It sh

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(

Hi,
any ideas how to implement TradingView Pine RMA ?