dataframe

Hello,
Considering your amazing efficiency on pandas, numpy, and more, it would seem to make sense for your module to work with even bigger data, such as Audio (for example .mp3 and .wav). This is something that would help a lot considering the nature audio (ie. where one of the lowest and most common sampling rates is still 44,100 samples/sec). For a use case, I would consider vaex.open('Hu

Are you using Python or Rust?

Python

Which feature gates did you use?

This can be ignored by Python users.

What version of polars are you using?

0.9.12

What operating system are you using polars on?

macOS

Describe your bug.

When reading a CSV file with variable number of columns, polars assumes all rows have the number of columns inferred from th

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()               

Which version are you running? The lastest version is on Github. Pip is for major releases.

0.3.14b0

Describe the bug
KeyError: 1

To Reproduce
Provide sample code.
df.ta.stc(append=True)

Expected behavior
Should work without crashing

Screenshots
If applicable, add screenshots to help explain your problem.

Additional context
You are

Indexes in DataFrame are not saved when exporting to csv using to_csv.

const df = new DataFrame(input, { index: ['A', 'B', 'C'] } );
df.to_csv(filename);

Is your feature request related to a problem or challenge? Please describe what you are trying to do.
There are some discussions in #1228

Describe the solution you'd like
like #1290

Describe alternatives you've considered
The task is mechanical, however, it is ideal for newcomers to familiarize themselves with datafusion's build, test, and PR processes.

**Additional context

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 ?

I'm using black and isort for other projects (see e.g. https://github.com/hyperopt/hyperopt/pull/748/files) and find them quite useful to have more consistent codebase. I think you should drop python3.5 support though, as black is python3.6+. Is this something you would be open to consider?