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:

Are you using Python or Rust?

Python

What version of polars are you using?

0.12.2

What operating system are you using polars on?

W10

Describe your bug.

Setting the config set_tbl_rows does not result in limited printing of dataframe

What are the steps to reproduce the behavior?

>>> import polars as pl
>>> df = pl.DataFrame({"a": [1,

Describe the bug

Failed to execute Series.drop_duplicates.

In [75]: a = md.DataFrame(np.random.rand(10, 2), columns=['a', 'b'], chunk_size=2)                  

In [76]: a['a'].drop_duplicates().execute()               

Pivot points are used to notice importance levels during a trading session. I have used them successfully for day trading as they are solid inflection points.

Read more here - https://tradingsim.com/blog/pivot-points/

Pivot Point (PP) = (Prior Daily High + Low + Close) / 3
R1 = (2 x Pivot Point) – Prior Daily Low
R2 = Pivot Point + (Prior Daily High – Prior Daily Low)
S1 = (2

Is your feature request related to a problem? Please describe.
The Series.map() function should enable the usage of index in the passed lambda, just like the normal Array.map() function does. My example use case is calculating a moving average, which requires referencing values next to the current position in the Series.

Describe the solution you'd like
I would like to be able to writ

Is your feature request related to a problem or challenge? Please describe what you are trying to do.
We would like to compute a power function (like 2**4 = 2 * 2 * 2 * 2) in datafusion

@matthewmturner asks for it here: apache/arrow-datafusion#147 (comment)

Describe the solution you'd like

Implement the power function as described in

Example:
In the image below the word starships should begin on a new line to avoid being split.

Terminal width is provided to determine how many columns to print. The terminal width or the total width of the column headers may be used to wrap the text in the footer.

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(