WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Atom Version: 0.174.0

OS: Windows 7 x64

My Atom Version is 0.174.0, but release note is always 0.158

Issue 2:
Install linter-jshint

Try doing some javascript

For some reason, these errors aren't occouring in other javascript files in the same session. Also, this is the same session that I installed linter-jshint on, through the GUI package installer in Edit > Preferences.

Atom Version: 0.165.0

System: linux 3.13.0-43-generic

Thrown From: Atom Core

Stack Trace

Uncaught Error: Cannot find module './load-config'

At module.js:346

Error: Cannot find module './load-config'
at Module._resolveFilename (module.js:344:15)
at Function.Module._resolveFilename (/usr/share/atom/resources/app/src/module-cache.js:380:52)
at Function.Module._load (module.js:286:25)
at Module.require (module.js:373:17)
at require (module.js:392:17)
at /home/athan/.atom/packages/jshint/node_modules/lazy-req/index.js:6:43
at lint (/home/athan/.atom/packages/jshint/index.js:156:34)
at delayed (/usr/share/atom/resources/app/node_modules/roaster/node_modules/cheerio/node_modules/lodash/dist/lodash.js:5408:27)

Commands

6x -6:52.9 core:backspace (input.hidden-input)
-6:50.5 core:confirm (input.hidden-input)
-6:44.8 core:undo (atom-workspace.workspace.scrollbars-visible-always.theme-seti-syntax.theme-seti-ui)
13x -6:34.8 core:move-right (input.hidden-input)
6x -6:33.8 core:backspace (input.hidden-input)
-6:32.0 core:confirm (input.hidden-input)
-6:10.6 editor:newline (input.hidden-input)
-5:52.7 core:backspace (input.hidden-input)
-5:44.8 core:save (atom-workspace.workspace.scrollbars-visible-always.theme-seti-syntax.theme-seti-ui)
3x -2:42.2 core:move-down (input.hidden-input)
-1:59.3 core:delete (input.hidden-input)
-1:59.2 core:move-down (input.hidden-input)
-1:56.9 editor:newline (input.hidden-input)
-1:18.3 core:save (input.hidden-input)
-0:59.3 core:confirm (input.hidden-input)
-0:00.0 core:save (input.hidden-input)

Config

{
"core": {
"themes": [
"seti-ui",
"seti-syntax"
]
},
"editor": {
"showIndentGuide": true,
"showInvisibles": true,
"softWrap": true,
"fontSize": 25,
"invisibles": {},
"softWrapAtPreferredLineLength": true
}
}

Installed Packages

# User
atom-beautify, v0.21.2
autocomplete-plus, v1.1.0
color-picker, v1.2.6
git-log, v0.2.0
ide-haskell, v0.3.0
javascript-snippets, v1.0.0
jsformat, v0.7.18
language-haml, v0.14.0
language-haskell, v1.0.0
language-javascript-semantic, v0.1.0
linter, v0.9.1
linter-csslint, v0.0.11
linter-erb, v0.0.3
linter-hlint, v0.3.1
linter-htmlhint, v0.0.8
linter-jshint, v0.1.0
linter-jsonlint, v0.1.2
minimap, v3.5.4
script, v2.16.0
seti-syntax, v0.2.1
seti-ui, v0.6.1
travis-ci-status, v0.11.1

# Dev
No dev packages
Issue 1:
🐛 Bug

To Reproduce

Steps to reproduce the behavior:

[root@ip-172-26-11-98 ~]# python3.9 -m pip install torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
Looking in links: https://download.pytorch.org/whl/torch_stable.html
ERROR: Could not find a version that satisfies the requirement torch==1.7.0+cpu (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2)
ERROR: No matching distribution found for torch==1.7.0+cpu

Expected behavior

Successful installation of torch

Environment

PyTorch Version (e.g., 1.0): 1.7

OS (e.g., Linux): CentOS 7.8

How you installed PyTorch (conda, pip, source): pip

Build command you used (if compiling from source):

Python version: 3.9

CUDA/cuDNN version:

GPU models and configuration:

Any other relevant information: I had built Python3.9 from source.

Additional context

I had built Python 3.9 this way:

yum install openssl-devel readline-devel libuuid-devel gdbm-devel sqlite-devel bzip bzip2-devel libffi-devel
wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tgz
tar -xzf Python-3.9.0.tgz
rm -rf Python-3.9.0.tgz
cd Python-3.9.0
mkdir build
cd build
../configure --sbindir=/usr/bin/python3.9
make
make install

Issue 2:
🐛 Windows LibTorch C++ Cannot Load CUDA Module

th.jit.trace()'ing or th.jit.script()'ing even just a Conv2d module will produce a serialized file that cannot be loaded by the C++ runtime. See the following two example scripts for a repro:

import torch as th
from torch import nn

d = th.nn.Conv2d(3, 3, 1, 1, 0).cuda()
z = th.zeros(1, 3, 256, 256).cuda()
th.jit.script(d).save("smod.ptj") # Also fails if this is th.jit.trace(d, (z,))

#include <iostream>
#include <torch/script.h>
int main() {
try {
auto mod = torch::jit::load("smod.ptj");
} catch(c10::Error& e) {
std::cerr << e.what() << std::endl;
return 1;
}
return 0;
}

To Reproduce

Steps to reproduce the behavior:

Run the above python script.

Compile + run the above C++ program.

The exception text is:

cuda_dispatch_ptr INTERNAL ASSERT FAILED at C:\w\1\s\windows\pytorch\aten\src\ATen/native/DispatchStub.h:70, please report a bug to PyTorch. DispatchStub: missing CUDA kernel (operator () at C:\w\1\s\windows\pytorch\aten\src\ATen/native/DispatchStub.h:70)
(no backtrace available)

and is thrown at include\ATen\core\TensorMethods.h:249 (the end of an inline copy_ method).

Problem persists with latest master builds as well.

I used linux to dump the module since installing pytorch from anaconda currently results in a pytorch that will not import:

from torch._C import *
ImportError: DLL load failed: The specified procedure could not be found.

Expected behavior

C++ program returns 0 w/no errors displayed.

Environment

PyTorch Version (e.g., 1.0): 1.2 stable (also nightly)

OS (e.g., Linux): Windows

How you installed PyTorch (conda, pip, source): conda (linux), pytorch.org (win binaries)

Build command you used (if compiling from source):

Python version: 3.7

CUDA/cuDNN version: 10.0 / 3.6

GPU models and configuration: Titan RTX

cc @peterjc123
Issue 1:
As shown in the example below, when passing in two series with the same name to concat you end up with duplicates of the last series passed in.

In [42]: pd.__version__
Out[42]: '0.10.1'

In [43]: dates = pd.date_range('01-Jan-2013','01-Dec-2013', freq='MS')
...: L = pd.TimeSeries('L', dates, name='LeftRight')
...: R = pd.TimeSeries('R', dates, name='LeftRight')
...:

In [44]: L
Out[44]:
2013-01-01 L
2013-02-01 L
2013-03-01 L
2013-04-01 L
2013-05-01 L
2013-06-01 L
2013-07-01 L
2013-08-01 L
2013-09-01 L
2013-10-01 L
2013-11-01 L
2013-12-01 L
Freq: MS, Name: LeftRight

In [45]: R
Out[45]:
2013-01-01 R
2013-02-01 R
2013-03-01 R
2013-04-01 R
2013-05-01 R
2013-06-01 R
2013-07-01 R
2013-08-01 R
2013-09-01 R
2013-10-01 R
2013-11-01 R
2013-12-01 R
Freq: MS, Name: LeftRight

In [46]: pd.concat([L,R], axis=1)
Out[46]:
LeftRight LeftRight
2013-01-01 R R
2013-02-01 R R
2013-03-01 R R
2013-04-01 R R
2013-05-01 R R
2013-06-01 R R
2013-07-01 R R
2013-08-01 R R
2013-09-01 R R
2013-10-01 R R
2013-11-01 R R
2013-12-01 R R

In [47]: pd.concat([L,R], axis=1, keys=['Left','Right'])
Out[47]:
Left Right
2013-01-01 L R
2013-02-01 L R
2013-03-01 L R
2013-04-01 L R
2013-05-01 L R
2013-06-01 L R
2013-07-01 L R
2013-08-01 L R
2013-09-01 L R
2013-10-01 L R
2013-11-01 L R
2013-12-01 L R

Issue 2:
Motivating from SO

This is the inverse of pd.get_dummies. So maybe invert_dummies is better?

I think this name makes more sense though.

This seems a reasonable way to do it. Am I missing anything?

In [46]: s = Series(list('aaabbbccddefgh')).astype('category')

In [47]: s
Out[47]:
0 a
1 a
2 a
3 b
4 b
5 b
6 c
7 c
8 d
9 d
10 e
11 f
12 g
13 h
dtype: category
Categories (8, object): [a < b < c < d < e < f < g < h]

In [48]: df = pd.get_dummies(s)

In [49]: df
Out[49]:
a b c d e f g h
0 1 0 0 0 0 0 0 0
1 1 0 0 0 0 0 0 0
2 1 0 0 0 0 0 0 0
3 0 1 0 0 0 0 0 0
4 0 1 0 0 0 0 0 0
5 0 1 0 0 0 0 0 0
6 0 0 1 0 0 0 0 0
7 0 0 1 0 0 0 0 0
8 0 0 0 1 0 0 0 0
9 0 0 0 1 0 0 0 0
10 0 0 0 0 1 0 0 0
11 0 0 0 0 0 1 0 0
12 0 0 0 0 0 0 1 0
13 0 0 0 0 0 0 0 1

In [50]: x = df.stack()

# I don't think you actually need to specify ALL of the categories here, as by definition
# they are in the dummy matrix to start (and hence the column index)
In [51]: Series(pd.Categorical(x[x!=0].index.get_level_values(1)))
Out[51]:
0 a
1 a
2 a
3 b
4 b
5 b
6 c
7 c
8 d
9 d
10 e
11 f
12 g
13 h
Name: level_1, dtype: category
Categories (8, object): [a < b < c < d < e < f < g < h]

NB. this is buggy ATM.

In [51]: Series(pd.Categorical(x[x!=0].index.get_level_values(1)),categories=df.categories)
Issue 1:
[x ] I have searched the issues of this repository and believe that this is not a duplicate.

No errors in development, but when I minify the bundle and hit ssr url, I receive this error:

https://reactjs.org/docs/error-decoder.html?invariant=149&args[]=iconMenuContainer

Tech
Version

Material-UI
0.19.2

React
16

browser

etc

Issue 2:
I'm using the onClick property for the DatePicker component and it works fine, the only issue is that my VSC typescript linter is indicating that it is not a part of the type definition for this component.

I have searched the issues of this repository and believe that this is not a duplicate.

Expected Behavior

No type errors would be fantastic - and this is the only one I've run into so far!

Current Behavior

This is the error I'm getting:

Property 'onClick' does not exist on type 'IntrinsicAttributes & IntrinsicClassAttributes<DatePicker> & Readonly<{ children?: ReactNode; }> ...'.

Steps to Reproduce (for bugs)

Have typescript setup in a react environment

Use import DatePicker from 'material-ui/DatePicker' to import the DatePicker. Right now, I'm getting around this error by using const DatePicker: any = require('material-ui/DatePicker'). Lame.

Add an onClick property to your DatePicker. Eg:

... onClick={ () => console.log('opening the datepicker') } ...

See annoying red stuff in your editor.

Context

Annoying typescript issue making me ask my boss annoying typescript questions. This is more an issue with typescript than you guys, but you've done a really awesome job so far, this is just a way to make it a little bit better.

Your Environment

We're running a react/redux/typescript app in Visual Studio Code. I installed the @types/material-ui file and it mostly works great, thanks for putting in all that work!

Tech
Version

Material-UI
0.20.0

React
16.2.0

browser

Visual Studio Code
1.19.1

@types/material-ui
0.20.1
Issue 1:
See the attachment. With ansible 1.7.2 this works as expected:

% ansible-playbook --version

ansible-playbook 1.7.2

% ansible-playbook -i hosts/localhost a.yml --tags b

PLAY [localhost]

GATHERING FACTS

ok: [localhost]

TASK: [debug msg="b"]

ok: [localhost] => {

"msg": "b"

}

PLAY RECAP

localhost : ok=2 changed=0 unreachable=0

failed=0

With 1.9.1 it's broken:

% ansible-playbook --version

ansible-playbook 1.9.1

% ansible-playbook -i hosts/localhost a.yml --tags b

ERROR: tag(s) not found in playbook: b. possible values:

Issue 2:
Issue Type:

Bug Report

Ansible Version:

1.8.1-1.el6

Environment:

CentOS release 6.6 (Final)

Summary:

Tags from includes are being ignored

Tags from within a playbook are working just fine.

After a downgrade to Ansible 1.7.2-2.el6 this is working

Steps To Reproduce:

include: someotherplaybook.yml tags=test_tag

ansible-playbook someplaybook.yml -e "target=somehost" -t test_tag

Expected Results:

Tags should not be ignored

Actual Results:

ERROR: tag(s) not found in playbook: test_tag. possible values:
Issue 1:
Description

Due to the complexity of our DAG, we only use the Graph view to manage it. It would be great if we could get the task group options (specifically clearing a task group - (see #26658, #28003).

Use case/motivation

No response

Related issues

No response

Are you willing to submit a PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct

Issue 2:
Apache Airflow version: 2.0.0

Kubernetes version (if you are using kubernetes) (use kubectl version): 1.18.10

Environment:

Cloud provider or hardware configuration: Azure AKS

OS (e.g. from /etc/os-release): Linux

Kernel (e.g. uname -a): Linux

Install tools: All

What happened:

While injecting execution date and previous execution date success as environment variables using macros the values are not rendered in the pod

What you expected to happen:

Values are correctly rendered in the pod so that I can use that in my task.

How to reproduce it:

Define Kubernetes environment variable like this

k8s_env_variable = k8s.V1EnvVar( name='execution_date_1', value='{{ ts }}' )

Inject it in the operator

KubernetesPodOperator(
namespace='airflow',
name=name,
task_id=name,
image="Use your dag image id",
env_vars=[k8s_env_variable],
image_pull_policy='Always',
get_logs=True,
log_events_on_failure=True,
resources=resources,
is_delete_operator_pod=True,
node_selector={'agentpool': 'airflowtasks'},
termination_grace_period=60
)

Print execution date in your dag

import os
print(os.getenv('execution_date'))

It should have printed the correct execution date instead of nothing.

If you are using kubernetes, please attempt to recreate the issue using minikube or kind.

Install minikube/kind

Minikube https://minikube.sigs.k8s.io/docs/start/

Kind https://kind.sigs.k8s.io/docs/user/quick-start/
Issue 1:
I'm not sure if this is a bug or corruption experienced during the upgrade but as of 1.2.0, we're now experiencing duplicate results in all queries:

{

took: 0

timed_out: false

_shards: {

total: 5

successful: 5

failed: 0

}

hits: {

total: 2

max_score: 13.58639

hits: [

{

_index: media6

_type: Media

_id: 534918829017389526_260014085,

_score: 13.58639,

_source: {}

},

{

_index: media6

_type: Media

_id: 534918829017389526_260014085,

_score: 12.815866,

_source: {}

}]

}}

There have been no changes to indexes, types, or other mappings. My understanding was that a unique ID really depends on index/type/id/routing. The routing, by

default, is derived from the ID. No parent-child relationships are in use here.

Cross-posted but unrelated to sort as initially suspected:

http://elasticsearch-users.115913.n3.nabble.com/Duplicate-Results-Following-Upgrade-to-1-2-0-amp-SortScript-td4056672.html

Issue 2:
Many people have some challenges when using Git/GitHub to contribute to the project.

It would be nice to have a GitHub.CHEATSHEET similar to GRADLE.CHEATSHEET.
Issue 1:
Bug report

Describe the bug

A clear and concise description of what the bug is.

To Reproduce

Steps to reproduce the behavior, please provide code snippets or a repository:

Clone https://github.com/tenjojeremy/test-nextjs-simple.git

run yarn

run yarn start

open localhost

you should see 3 posters

run now

open production site

you will see a 500 error

open runtime logs in your dashboard

see

Expected behavior

Should display 3 movie posters in production not a 500 error

Issue 2:
Feature request

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

It's currently not possible to read files from API routes or pages.

Describe the solution you'd like

I want to be able to call fs.readFile with a __dirname path and have it "just work".

This should work in Development and Production mode.

Describe alternatives you've considered

This may need to integrate with @zeit/webpack-asset-relocator-loader in some capacity. This plugin handles these types of requires.

However, it's not a necessity. I'd be OK with something that only works with __dirname and __filename (no relative or cwd-based paths).

Additional context

Example:

// pages/api/test.js
import fs from 'fs'
import path from 'path'

export default (req, res) => {
const fileContent = fs.readFileSync(
path.join(__dirname, '..', '..', 'package.json'),
'utf8'
)
// ...
}

Note: I know you can cheat the above example ☝️ with require, but that's not the point. 😄
Issue 1:
Daigo Kobayashi opened SPR-2657 and commented

There is no way to display success message(s) like struts' ActionMessage. Spring should provide Messages inteface in a similar way of Errors and related tag libraries.

Issue Links:

#11130 Flash Scope for Spring MVC (Without Spring Web Flow) ("duplicates")

12 votes, 12 watchers

Issue 2:
Andy Wilkinson opened SPR-9255 and commented

I've been bitten in the past by an intermittent BeanCurrentlyInCreationException when I've @Autowired a FactoryBean implementation. I believe that this is considered to be a no-no, but occassionally I forget and lose hours to diagnosing the problem until the penny drops. An example can be seen in https://issuetracker.springsource.com/browse/VMS-604. Today, I've been bitten by a variation of this same problem.

This time, rather than having an @Autowired FactoryBean I've got an @Autowired class that's a dependency of the FactoryBean. I believe this means that to avoid a possible BeanCurrentlyInCreationException I need to avoid using @Autowired on a FactoryBean and also on anything in the FactoryBean's dependency graph.

The main problem here is the intermittent nature of the failure. There appears to be something non-deterministic in the code that finds all of the candidates for a dependency. This, I'm guessing, is what makes the failure intermittent which, in turn, makes it harder to diagnose. I'm also wondering how Spring guarantees that there's only one possible candidate for the dependency if it, apparently, doesn't always need to initialise the FactoryBean to satisfy the dependency. Is there a risk that it might miss the fact that there are multiple candidates, or is there something about one ordering which means that it can successfully initialise the FactoryBean to check the type that it will produce without also triggering a BeanCurrentlyInCreationException?

Ideally, dependency resolution would be deterministic so that this problem happen none of the time or all of the time. Right now it's dangerous as the problem can be lurking for days or weeks until it occurs. If deterministic dependency resolution isn't possible, I'd love to see some improved diagnostics for this problem. Something that pointed out the dangerous use of @Autowired on a FactoryBean or one of its dependencies would be a big help.

Affects: 3.1 GA

Issue Links:

#13346 Doc: @Autowired properties not reliably set in FactoryBean before getObject ("duplicates")

Referenced from: commits spring-attic/spring-framework-issues@6fa97fa, spring-attic/spring-framework-issues@189ba5b

2 votes, 4 watchers
Issue 1:
Hello,

My issue is about lowpass generated in sos form

>>> print(signal.butter(2, 1, 'low', analog=True, output = "sos"))
>>> print(signal.butter(2, 1, 'high', analog=True, output = "sos"))
[[1. 0. 0. 1. 1.41421356 1. ]]
[[1. 0. 0. 1. 1.41421356 1. ]]

As you can see generating a lowpass and a highpass gives the same coefficients.

Same issue with the cheby1 filter type.

Like the sos configuration doesn't like to see b2 = 0

Cheers,

Issue 2:
Hello,

I have realized about an issue with sparse matrixes and loadmat function.

I have a set of sparse matrixes for storing very sparse values. Sometimes they are so sparse that some of the matrixes are never used, so they keep on zeros.

When I try to save them in a matlab file and load them again I always find the same problem, invalid shape. I know that the sparse matrixes should have at leas 1 element, and 2 dimensions, but the content of the matrixes is data-driven.

My point is that is not real the sparse has no shape, it is just there is no active elements in that moment. Is this a known feature? it is a new bug?

Thabks for your help and sorry if it is duplicated, but I didn't find any other issue with a similar description.
Issue 1:
I tried using the @types/express-sessions package and had problems.

I tried using the next stable version of tsc "typescript": "3.8.3"

I am tryng to use express-sessions in my app, but have next error after yarn add @types/express-sessions

Can anybodt help me? ts version: 3.8.3, express version: 4.17.1

Authors: @TheHandsomeCoder, @donnut, @mdekrey, @mrdziuban, @sbking, @afharo, @teves-castro, @1M0reBug, @hojberg, @samsonkeung, @angeloocana, @raynerd, @moshensky, @ethanresnick, @deftomat, @blimusiek, @biern, @rayhaneh, @rgm, @drewwyatt, @jottenlips, @minitesh, @Krantisinh, @pirix-gh, @brekk, @Nemo108, @jituanlin, @Philippe-mills, @Saul-Mirone

If you do not mention the authors the issue will be ignored.

Issue 2:
Hi! Have next dep in my package.json file: "express": "4.17.1", "@types/express": "4.17.3", "express-session": "1.17.1".

Now I'm trying to add "@types/express-session": "1.17.0" but have the next errors in console.

Can anybody help me?

Authors: @TheHandsomeCoder, @donnut, @mdekrey, @mrdziuban, @sbking, @afharo, @teves-castro, @1M0reBug, @hojberg, @samsonkeung, @angeloocana, @raynerd, @moshensky, @ethanresnick, @deftomat, @blimusiek, @biern, @rayhaneh, @rgm, @drewwyatt, @jottenlips, @minitesh, @Krantisinh, @pirix-gh, @brekk, @Nemo108, @jituanlin, @Philippe-mills, @Saul-Mirone
Issue 1:
It is required to obtain Lagrangian multipliers while optimizing a linear programming problem. Kindly help.

Best regards,

Bharat

Issue 2:
I have a huge linprog problem of almost 1k variables and restrictions. I can calculate the solution with scipy.optimize.linprog(method='simplex') but I need shadow prices (or opportunity costs / duals) of ~100 inequalities.

I'm able to calculate them by adding 1 to the right side of the inequality and then solving that problem. Then I get the shadow price substracting the objective functions values for both solutions: shadow_price_i = f_max_original - f_max_i. Then repeat 100 times. This method works but it's painfully slow (1h). Note: I could also pose the dual problem and solve it

It's a shame that scipy does not return duals, so I'm opening a feature request. I'm new contributing to open projects, but I'm a CS graduate and have experience with both python and the simplex method, so I may be able to do so with some guidance.
Issue 1:
Bug report

Bug summary

Can't use qt4agg, error reported below.

Downgrade to matplotlib 3.1.3 solves the problem.

Code for reproduction

import matplotlib as mpl
mpl.use('qt4agg')

Or, set it to Qt4Agg in matplotlibrc file.

Actual outcome

ImportError: cannot import name '_isdeleted'
Failed to enable GUI event loop integration for 'qt5'

Matplotlib version

Operating system: win 10 LTSC 2019

Matplotlib version: 3.2.1

Matplotlib backend (print(matplotlib.get_backend())): can only use TkAgg

Python version: 3.6

Issue 2:
Bug report

After updating to latest version (3.2.1) I started getting this error:

# Paste your code here
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
>>>from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
Traceback (most recent call last):
File "<pyshell#0>", line 1, in <module>
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
File "C:\Python37-32\lib\site-packages\matplotlib\backends\backend_qt4agg.py", line 5, in <module>
from .backend_qt5agg import (
File "C:\Python37-32\lib\site-packages\matplotlib\backends\backend_qt5agg.py", line 11, in <module>
from .backend_qt5 import (
File "C:\Python37-32\lib\site-packages\matplotlib\backends\backend_qt5.py", line 19, in <module>
from .qt_compat import (
ImportError: cannot import name '_isdeleted' from 'matplotlib.backends.qt_compat' (C:\Python37-32\lib\site-packages\matplotlib\backends\qt_compat.py)

Matplotlib version

Operating system: Windows 10

Matplotlib version: 3.2.1

Matplotlib backend (print(matplotlib.get_backend())):TkAgg

Python version:3.7.6 (32Bit)

Jupyter version (if applicable):

Other libraries:

altgraph 0.17

astroid 2.3.3

colorama 0.4.3

cx-Freeze 6.1

cycler 0.10.0

future 0.18.2

isort 4.3.21

joblib 0.14.1

kiwisolver 1.1.0

lazy-object-proxy 1.4.3

matplotlib 3.2.1

mccabe 0.6.1

mpmath 1.1.0

numpy 1.18.2+mkl

pandas 1.0.3

pefile 2019.4.18

pip 20.0.2

psutil 5.7.0

PyInstaller 4.0.dev0+d08a42c612

pylint 2.4.4

pyparsing 2.4.6

PyQt4 4.11.4

PyQt5-sip 12.7.1

python-dateutil 2.8.1

pytz 2019.3

pywin32-ctypes 0.2.0

scikit-learn 0.22.2.post1

scipy 1.4.1

setuptools 46.0.0

six 1.14.0

tailer 0.4.1

typed-ast 1.4.1

wrapt 1.12.1

xlrd 1.2.0

XlsxWriter 1.2.8