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jupyter | Jupyter metapackage for installation , docs and chat | Data Visualization library

by jupyter Python Version: Current License: BSD-3-Clause

by jupyter Python Version: Current License: BSD-3-Clause

kandi X-RAY | jupyter Summary

jupyter is a Python library typically used in Analytics, Data Visualization, Jupyter applications. jupyter has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can download it from GitHub.

Jupyter metapackage for installation and docs.

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jupyter has a highly active ecosystem.
It has 13986 star(s) with 3612 fork(s). There are 659 watchers for this library.
It had no major release in the last 6 months.
There are 192 open issues and 190 have been closed. On average issues are closed in 88 days. There are 7 open pull requests and 0 closed requests.
It has a negative sentiment in the developer community.
The latest version of jupyter is current.

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jupyter has 0 bugs and 0 code smells.

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jupyter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
jupyter code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.

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license License

jupyter is licensed under the BSD-3-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.

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Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
jupyter saves you 56 person hours of effort in developing the same functionality from scratch.
It has 213 lines of code, 3 functions and 5 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.

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jupyter Key Features

Jupyter metapackage for installation, docs and chat

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Community Discussions

Trending Discussions on jupyter

Compute class weight function issue in 'sklearn' library when used in 'Keras' classification (Python 3.8, only in VS code)
How to Export Jupyter Notebook by VSCode in PDF format? (Windows 10)
How to undo/redo changes inside the selected cell in Jupyter notebook?
iPyKernel throwing "TypeError: object NoneType can't be used in 'await' expression"
"Attempting to perform BLAS operation using StreamExecutor without BLAS support" error occurs
Running cells with Python 3.10 requires ipykernel installed
ipykernel (Jupyter notebook/labs) cannot import name ''filefind" from traitlets.utils
lfortran in a jupyter notebook kills kernel
Pandas - How to Save A Styled Dataframe to Image
embedding jupyter notebook/ google colab in Django app

Trending Discussions on jupyter

QUESTION

Compute class weight function issue in 'sklearn' library when used in 'Keras' classification (Python 3.8, only in VS code)

Asked 2022-Mar-27 at 23:14

The classifier script I wrote is working fine and recently added weight balancing to the fitting. Since I added the weight estimate function using 'sklearn' library I get the following error :

compute_class_weight() takes 1 positional argument but 3 were given

This error does not make sense per documentation. The script should have three inputs but not sure why it says expecting only one variable. Full error and code information is shown below. Apparently, this is failing only in VS code. I tested in the Jupyter notebook and working fine. So it seems an issue with VS code compiler. Any one notice? ( I am using Python 3.8 with other latest other libraries)

from sklearn.utils import compute_class_weight

train_classes = train_generator.classes

class_weights = compute_class_weight(
                                        "balanced",
                                        np.unique(train_classes),
                                        train_classes                                                    
                                    )
class_weights = dict(zip(np.unique(train_classes), class_weights)),
class_weights

In Jupyter Notebook,

ANSWER

Answered 2022-Mar-27 at 23:14

After spending a lot of time, this is how I fixed it. I still don't know why but when the code is modified as follows, it works fine. I got the idea after seeing this solution for a similar but slightly different issue.

class_weights = compute_class_weight(
                                        class_weight = "balanced",
                                        classes = np.unique(train_classes),
                                        y = train_classes                                                    
                                    )
class_weights = dict(zip(np.unique(train_classes), class_weights))
class_weights

Source https://stackoverflow.com/questions/69783897

QUESTION

"Attempting to perform BLAS operation using StreamExecutor without BLAS support" error occurs

Asked 2022-Feb-21 at 16:09

my computer has only 1 GPU.

Below is what I get the result by entering someone's code

[name: "/device:CPU:0" device_type: "CPU" memory_limit: 268435456
locality {} incarnation: 16894043898758027805, name: "/device:GPU:0"
device_type: "GPU" memory_limit: 10088284160
locality {bus_id: 1 links {}}
incarnation: 17925533084010082620
physical_device_desc: "device: 0, name: GeForce RTX 3060, pci bus id: 0000:17:00.0, compute 
capability: 8.6"]

I use jupyter notebook and I run 2 kernels now. (TensorFlow 2.6.0 and also installed CUDA and cuDNN as TensorFlow guide)

The first kernel is no problem to run my Sequential model from Keras.

But when I learn the same code in the second kernel, I got the error as below.

Attempting to perform BLAS operation using StreamExecutor without BLAS support [[node sequential_3/dense_21/MatMul (defined at \AppData\Local\Temp/ipykernel_14764/3692363323.py:1) ]] [Op:__inference_train_function_7682]

Function call stack: train_function

how can I learn multiple kernels without any problem and share them with only 1 GPU?

I am not familiar with TensorFlow 1.x.x version though.

I just solved this problem as below. This problem is because when keras run with gpu. It uses almost all vram. So i needed to give memory_limit for each notebook. Here is my code how i could solve it. You can just change memory_limit value.

gpus = tf.config.experimental.list_physical_devices('GPU')
if gpus:
  try:
    tf.config.experimental.set_virtual_device_configuration(
        gpus[0],[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=5120)])
  except RuntimeError as e:
    print(e)

ANSWER

Answered 2021-Oct-12 at 08:52

For the benefit of community providing solution here

This problem is because when keras run with gpu, it uses almost all vram. So we needed to give memory_limit for each notebook as shown below

gpus = tf.config.experimental.list_physical_devices('GPU')
if gpus:
  try:
    tf.config.experimental.set_virtual_device_configuration(
        gpus[0],[tf.config.experimental.VirtualDeviceConfiguration(memory_limit=5120)])
  except RuntimeError as e:
    print(e)

(Paraphrased from MCPMH)

Source https://stackoverflow.com/questions/69401285

QUESTION

Running cells with Python 3.10 requires ipykernel installed

Asked 2022-Feb-09 at 09:03

I just installed Python 3.10 on my laptop (Ubuntu 20.04).

Running a Jupyter Notebook inside of VS Code works with Python 3.9 but not with Python 3.10. I get the error message: Running cells with 'Python 3.10.0 64 bit' requires ipykernel installed or requires an update.

Update February 2022

Jalil Nourmohammadi Khiarak gave a more complete answere, it is now the new accepted answer.

Update January 2022

It was a dumb error, I solved my problem (see accepted answer).

Things I tried:

Clicking on reinstall, which runs:

/usr/bin/python3.10 /home/joris/.vscode/extensions/ms-python.python-2021.10.1365161279/pythonFiles/shell_exec.py /usr/bin/python3.10 -m pip install -U --force-reinstall ipykernel /tmp/tmp-12568krFMIDJVy4jp.log

Running pip3 install --upgrade ipykernel jupyter notebook pyzmq (from this thread).

Edits

As asked in the comments, here is the output when I click the "reinstall" button:

/usr/bin/python3.10 /home/joris/.vscode/extensions/ms-python.python-2021.10.1365161279/pythonFiles/shell_exec.py /usr/bin/python3.10 -m pip install -U --force-reinstall ipykernel /tmp/tmp-10997AnLZP3B079oV.log
Executing command in shell >> /usr/bin/python3.10 -m pip install -U --force-reinstall ipykernel
Traceback (most recent call last):
  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/usr/lib/python3/dist-packages/pip/__main__.py", line 19, in <module>
    sys.exit(_main())
  File "/usr/lib/python3/dist-packages/pip/_internal/cli/main.py", line 73, in main
    command = create_command(cmd_name, isolated=("--isolated" in cmd_args))
  File "/usr/lib/python3/dist-packages/pip/_internal/commands/__init__.py", line 96, in create_command
    module = importlib.import_module(module_path)
  File "/usr/lib/python3.10/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "/usr/lib/python3/dist-packages/pip/_internal/commands/install.py", line 24, in <module>
    from pip._internal.cli.req_command import RequirementCommand
  File "/usr/lib/python3/dist-packages/pip/_internal/cli/req_command.py", line 15, in <module>
    from pip._internal.index.package_finder import PackageFinder
  File "/usr/lib/python3/dist-packages/pip/_internal/index/package_finder.py", line 21, in <module>
    from pip._internal.index.collector import parse_links
  File "/usr/lib/python3/dist-packages/pip/_internal/index/collector.py", line 12, in <module>
    from pip._vendor import html5lib, requests
ImportError: cannot import name 'html5lib' from 'pip._vendor' (/usr/lib/python3/dist-packages/pip/_vendor/__init__.py)
Traceback (most recent call last):
  File "/home/joris/.vscode/extensions/ms-python.python-2021.10.1365161279/pythonFiles/shell_exec.py", line 26, in <module>
    subprocess.check_call(shell_args, stdout=sys.stdout, stderr=sys.stderr)
  File "/usr/lib/python3.10/subprocess.py", line 369, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['/usr/bin/python3.10', '-m', 'pip', 'install', '-U', '--force-reinstall', 'ipykernel']' returned non-zero exit status 1.

Here is what my _vendor folder contains:

joris@joris-N751JK:~$ ls /usr/lib/python3/dist-packages/pip/_vendor/
__init__.py  __pycache__

Here is the output of reinstalling pip and checking the _vendor file:

joris@joris-N751JK:~$ python3 -m pip install --upgrade --force-reinstall pip
Defaulting to user installation because normal site-packages is not writeable
Collecting pip
  Using cached pip-21.3.1-py3-none-any.whl (1.7 MB)
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 21.3.1
    Uninstalling pip-21.3.1:
      Successfully uninstalled pip-21.3.1
Successfully installed pip-21.3.1
joris@joris-N751JK:~$ ls /usr/lib/python3/dist-packages/pip/_vendor
__init__.py  __pycache__

ANSWER

Answered 2021-Nov-02 at 20:03

I don't think ipykernel is compatible with 3.10.

Below is the message I receive when I try to install ipykernel with the following command: conda install -c anaconda ipykernel

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - ipykernel -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0|>=3.5,<3.6.0a0|>=3.9,<3.10.0a0']

Your python: python=3.10

Solution:

I recommend creating a virtual environment using conda or another library.

To get you started:

Install Anaconda.
Enter the following commands. [Note: These are the Windows commands - may vary slightly on Mac and Linux.]

# Create virtual environment
# Use a version of Python that is less than 3.10
conda create --name your_env_name python<3.10

# Activate new environment
conda activate your_env_name

# Install ipykernel
conda install -c anaconda ipykernel

# Add this new environment to your Jupyter Notebook kernel list
ipython kernel install --name your_env_name --user

# Windows only: When trying to launch `jupyter notebook`, you may receive a win32api error.
# The command below fixes that issue.
conda install -c anaconda pywin32

Source https://stackoverflow.com/questions/69785084

QUESTION

Pandas - How to Save A Styled Dataframe to Image

Asked 2022-Jan-01 at 17:04

I have styled a dataframe output and have gotten it to display how I want it in a Jupyter Notebook but I am having issues find a good way to save this as an image. I have tried https://pypi.org/project/dataframe-image/ but the way I have this working it seem to be a NoneType as it's a styler object and errors out when trying to use this library.

This is just a snippet of the whole code, this is intended to loop through several 'col_names' and I want to save these as images (to explain some of the coding).

import pandas as pd
import numpy as np

col_name = 'TestColumn'

temp_df = pd.DataFrame({'TestColumn':['A','B','A',np.nan]})

t1 = (temp_df[col_name].fillna("Unknown").value_counts()/len(temp_df)*100).to_frame().reset_index()
t1.rename(columns={'index':' '}, inplace=True)
t1[' '] = t1[' '].astype(str) 

display(t1.style.bar(subset=[col_name], color='#5e81f2', vmax=100, vmin=0).set_table_attributes('style="font-size: 17px"').set_properties(
    **{'color': 'black !important',
       'border': '1px black solid !important'}
).set_table_styles([{
    'selector': 'th',
    'props': [('border', '1px black solid !important')]
}]).set_properties( **{'width': '500px'}).hide_index().set_properties(subset=[" "], **{'text-align': 'left'}))

[OUTPUT]

ANSWER

Answered 2022-Jan-01 at 17:04

Was able to change how I was using dataframe-image on the styler object and got it working. Passing it into the export() function rather than calling it off the object directly seems to be the right way to do this.

The .render() did get the HTML but was often losing much of the styling when converting it to image or when not viewed with Ipython HTML display. See comparision below.

Working Code:

import pandas as pd
import numpy as np
import dataframe_image as dfi

col_name = 'TestColumn'

temp_df = pd.DataFrame({'TestColumn':['A','B','A',np.nan]})

t1 = (temp_df[col_name].fillna("Unknown").value_counts()/len(temp_df)*100).to_frame().reset_index()
t1.rename(columns={'index':' '}, inplace=True)
t1[' '] = t1[' '].astype(str) 


style_test = t1.style.bar(subset=[col_name], color='#5e81f2', vmax=100, vmin=0).set_table_attributes('style="font-size: 17px"').set_properties(
    **{'color': 'black !important',
       'border': '1px black solid !important'}
).set_table_styles([{
    'selector': 'th',
    'props': [('border', '1px black solid !important')]
}]).set_properties( **{'width': '500px'}).hide_index().set_properties(subset=[" "], **{'text-align': 'left'})

dfi.export(style_test, 'successful_test.png')

Source https://stackoverflow.com/questions/70546823

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install jupyter

You can download it from GitHub.
You can use jupyter like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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