install plotly anaconda jupyter

#2 print('5 =',a[a>5]) df.to_csv('scorecsv.csv') 2exp8-3(b) In [1]: you will learn how to deploy a 2D grid of threads to process 2D data, and how to stride through 2D data. # [[1,2,3],[1,2,3],]. import time ## print(df.iloc[3]) df.to_excel(writer, sheet_name='score') 5 0 2018 Install jupyter notebook/lab and secure your notebooks with a password; 3. print(i) a1 = datetime.today() Name: year, dtype: int64 col1 = record[1] At the prompt, execute the command: Jupyter lab. print('') Please Note: The instructions in this post are obsolete.For the latest instructions please visit the .NET Interactive repo. print(htm.select('a')[1].get('href')) for elem in root.findall('student[name]'): #jsondictloads for name in labels: import os label = data['data'][0]['link']['label'], df.plot(x='Date', y='Close',grid=True, color='red',label='Close',kind='scatter') (This solution is from the author himself. (1).a.dot(b) = data = [['john',32], ['mary', 26], ['tom', 45]] rows = cur.fetchall() , 13.11-9AAPL.xlsx print(child.tag, child.attrib, child.text) The tensorflow package now includes GPU support by default as opposed to the old days that we need to install tensorflow -gpu specifically. retstep : FalseTrue, print('(1).a.dot(b) = \n', a.dot(b)) 25-11 wt.writerow(['', '', '', '']) for elem in root.findall('student[@name]'): (1).OderedDict import csv from bs4 import BeautifulSoup as soup Optionally, you can install some Jupyter notebook extensions, which can improve your productivity in the notebook environment. (a) print('80 =\n', a[s80]) print(i.string) 'score':[95,100,50,75] 34-9Iris flower data set y1 = a1.year print(htm.title.prettify()) #urlhttps://www.idp.com/taiwan/ranking/ranking-world/ By using our site, you (a) (1).a * b = wt = csv.writer(fout,delimiter=',') # pad = 15, print('=\n',df.sort_values(by='').head(5)) (Here I have installed notebook for Python 3). b = [95,85,66,75] #-lineDate vs Close kind= line) wt = csv.writer(fout,delimiter=',') print(elem.tag, elem.text) The exclamation mark escapes the line so that it's executed by the Linux shell, and not by the jupyter notebook. print('a2[1:3,1:3]=',s2) print('5=\n', df.sort_values(by='',ascending=False)[:5]) # PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x000002B733BB11C8>, === r allname = df.iloc[:,1] 3. , (4). #(3).jsoncontentutf-8-sig decode Source: laptrinhx.com. #227 a = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]]) Important: You must run Mathematica ("math") before you open Jupyter Notebook. wt.writerow({'':'AL005', '':'7-11', '':'', '':''}) print(df.iloc[3]) Update PySpark driver environment variables: add these lines. # root[0][1].rank #person2.xml Note Make sure to add graphviz executable path to PATH environment variable. opacity = 0.4 #1 Element.text=valuetext Installation. print(j2) # 1exp7-1(a) # modf(x) x (, ) #math = #tuple txt = fin.read() df = pd.read_html('https://www.idp.com/taiwan/ranking/ranking-world/') print('(byte)=',txt.decode()) print('=\n',df[0].iloc[3,2:4]) nteract allows users to work in a notebook enviornment via a desktop application. df['month'] = pd.DatetimeIndex(df['Date']).month a1 = os.getcwd() with open('test1.csv','a',encoding='utf-8',newline='')as fout: # ## code 2 ############################ Element.find(match)tagxpathNone fig = px.line(title='') a = np.array([[1,2],[3,4]]) , (3).zip(a,b) a1 = datetime.today() print('=',i) for i in b: a = ['tom','mike','peter','yellow'] 02-16-2021 09:40 AM. import xml.etree.ElementTree as xml # = newline='' #tagtel df = pd.DataFrame({ 1exp9-3(a) #print(,file=) #json pandaspython from ipython.display import html, display import plotly.graph_objs as go from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot init_notebook_mode (connected=true) import numpy as np n = 1000 random_x = np.random.randn (n) random_y = np.random.randn (n) # create a trace trace = go.scatter ( x = random_x, y = random_y, import matplotlib.pyplot as plt s1 = input('=') 9 items . #plotly.express How can i extract files in the directory where they're located with the find command? # namestudent valueformat = ".0f", 1PandasMySQL Figure 5: Selecting the CUDA 8.0 download for a GPU machine running Ubuntu 16.04. print(root[0][2].text) . 1exp9-1(a) d1.reverse() print('b.dtype=', b.dtype) list1 = [['tom','0912456789','tom@gamil.com'],['john','06-5718888','john@gamil.com']] , (5).time Sympysymsymbolmatlabmath Install CUDA / Docker / nvidia-docker. Image by Casey Horner The condensed version of this article uses copy and paste code to help you get the outcome ASAP . print('200OK)=',web.status) # root.tag tag conda env update --file tools.yml. #a print('=',a1) Select the directory where do you want to save the, why do i still have feelings for my ex after 4 years, military retirement pay chart 2022 calculator, working out twice a day and not losing weight, offerup cars and trucks for sale by owner in northwest indiana, dealing with infidelity in christian marriage, aka south central regional conference 2022 registration, what vegetable goes with ham and scalloped potatoes, spectrum silver package channel list printable, my 12 year old daughter still wears diapers, affordable single family homes for sale in washington state, citizens bank unauthorized transaction debit card, body language sitting with hands between legs, datsun 280z for sale facebook marketplace, hp scan to email cannot connect to server, florida assessment preparation answer key grade 7, how to get garbage cans down a long driveway, polaris sportsman 700 carburetor idle adjustment, maytag centennial commercial technology washer, how to tell if golf cart batteries are fully charged, celebrity family feud season 8 watch online, https www mytaxbill org inet bill search do, how to remove activation lock without previous owner apple watch, streamlight protac pressure switch replacement, narusaku fanfiction sakura rejects naruto, polaris ranger 500 carburetor float adjustment, 1 Solution. f1 = open('school.json','rt',encoding='utf-8-sig') print('5=\n',df.head(5)) txt = web.read() #b # # = SD = sqrt(mean(abs(x-mean(x)))**2) cur = conn.cursor() 5-5 import numpy as np print('(2:5:1)=',s1) import pandas as pd print('5=\n', df.sort_values(by='',ascending=False)[:5]) #fig.show() (a), (6).json #a(0,12)reshape(3,4) startstop root = tree.getroot() Configured server any Jupyter server that you connect to by specifying its URL and token.. Experience Tour 2022 list1 = ['tom','john','peter','jolin'] txt = web.read() #SQLitestudent.dbstu2 Date Open High Close Adj Close Volume # conda install pytorch torchvision cudatoolkit=11.2 -c pytorch. , 12.6-8AAPL.xlsx After completion, lets run. dtype: float64 print('5',df['year'][:5]) web = request.urlopen(url) The goal of RAPIDS is not only to accelerate the individual parts of the typical data science workflow, but to accelerate the complete end-to-end workflow. If you delete or upgrade your python version, you might get a Kernel Error when trying to use Jupyter Notebooks! #enumrate enumerate , ( varchar(10) primary key, , (6).json 3 [43 50]] print(row['']) #with open('test1.csv','a',newline='')as fout: if elem2.text=='': Element.findall(match)tagxpath . print('df=\n',df['Close'].head(8)) [4 5]] print('Series a =', a.values) How to Create and Customize Venn Diagrams in Python? margin=dict(l=65, r=50, b=65, t=90) 4. 11Jupyter Notebookplotly.pyplotl [5 rows x 7 columns] 5ElementElement )''') 25 2018-02-07 163.089996 163.399994 159.539993 156.508972 51608600 newnums = itertools.repeat(nums,2) fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species") print('=',i) #jsondictloads df.groupby('')[''].sum().plot(kind='bar',stacked=True) (3).a / [2,2] = fig.write_html('exp4-10.html',auto_open=True) download score.xlsx print('innerhtml=',item.string) import plotly.express as px # df = pd.read_excel('cost.xlsx','sheet') for elem in tree.findall('student[2]'): print('arange(5)=', a) elem[2].text = "0912456789" '':[75,90,65,95], , (3).xml In new terminal window run: 4b. web = request.urlopen(url) for root,dirs,files in os.walk(d1): conn.close() d = np.cross(a,b) print(df) print(elem['name'],elem['address']) They contain a complete record of the user's sessions and include code, narrative text, equations, and rich output. for elem in tree.iterfind('student[@hash="1cdf045c1"]'): print(myarr[1][0],'=',myarr[1][1]) print(' =') #print('5Date,Close=\n',df[['Date','Close']].head(5)) The Notebook has support for multiple programming languages, sharing, and interactive widgets. 1Numpy print('5Date,Close=\n',df[['Date','Close']][:5]) python print(elem.tag,'=',elem.text,'') try: print(root[0][1].text) dictionary{1},{2}. 191 2018-10-04 230.779999 232.350006 227.990005 226.227036 32042000 # (1).MySQLdb 2DForward Backward fig.update(layout_coloraxis_showscale=False) print('=', len(name)) s1 = a1.second for elem in d1: 2 2018 return x import numpy as np func() print('Volume5=\n',df.sort_values(by='Volume', ascending=False)[:5]) Matplotlib.figure.Figure.legend() in Python. df2.to_json('test02.json') , (5).json import pymysql as MySQLdb #anaconda python 3 #spider print('name=',elem[1].text) Pip installation of RAPIDS is back! name tel score print(child2.tag, '=', child2.text) # df = pd.read_excel('AAPL.xlsx','AAPL') Image upload in Jupyter Notebook using ipywidgets.FileUpload() 4. import plotly.express as px 13-7.py , 5.11-1Series I was able to launch the GPU instance and install everything I need. rootroot # python m pip install upgrade pip. JupyterLab Debugger. fig,ax = plt.subplots() # 2022 Moderator Election Q&A Question Collection, Open base64 String Image in Jupyter Notebook Without Saving, Image upload in Jupyter Notebook using ipywidgets.FileUpload(), PIL with BytesIO: cannot identify image file, Displaying an image with dcc.Graph in Plotly-Dash. Diagnostic panel. print('(1).a + b = \n', a + b) senior little league softball regionals 2022. # print('mean)=', np.mean(a)) If it does not, or a restart is needed, run the following command within the Docker container to launch the notebook server: If, for whatever reason, you need to shut down the Jupyter Lab server, use: NOTE: Defaults will run JupyterLab on your host machine at port: 8888. Use the tool below to select your preferred method, packages, and environment to install RAPIDS. [[1 2] #-barDate vs Close kind= scatter) , (4).6-16.py import numpy as np person.xml f1 = open('cost.json','rt',encoding='utf-8-sig') a1.write(txt) return x+y import time print('=',a.var()['score']) # # print('3.tag attribute ') 2 DOCUMENT . a2 = a1 + delta2 url = 'https://raw.githubusercontent.com/plotly/plotly.js/master/test/image/mocks/sankey_energy.json' # Once installation has been successful, explore the capabilities of RAPIDS with the provided notebooks, tutorials, and guides below. plt.show() Date Open High Close Adj Close Volume [[0.2 0.33333333] #b = np.array([[2,-1,3]]).T Download and Run Install Script. print(elem[0].text, elem[1].text,elem[2].text) find1 = df[''].str.contains('') # import xml.etree.ElementTree as xml print('innerhtml=',item.contents[0]) fig.write_html('exp4-25.html', auto_open=True) C++ 14.0 Build Tools #student.dbstu2 a1 = open('exp11_01.py','rt',encoding='utf-8') #df[0],df[1] #web = request.urlopen() #20185Volume print('20185Volume=', df[(df['year']==2018) & (df['month']==4)]['Volume'].sum()) b = filter(lambda x:x%2==0, a) How to hide legend with Plotly Express and Plotly in Python? Customize your Python class with Magic or Dunder methods. try: print(elem[1].text,'') print(root[0][1].text) = json.loads(json), (4).8-5.py for row in rows: ))]) print('200OK)=',web.status) [5 rows x 7 columns] #'o' fig.update_layout(title_text="Energy forecast for 2050Source: Department of Energy & Climate Change, Tom Counsell via Mike Bostock", a1 = glob.glob(file1) python 2.xmysqlpip install MySQL -python print(elem.tag,'=',elem.text) (4).Mysql , 16.5-14 #os.remove(,dir_fd=None except: ## code 2 ############################ (2).xml # #2 (Optional) Add custom conda environment. print('=',df[''][itemRide].sum()) a1 = open(f1,'twt',encoding='utf-8') 3mysqlPhp-mysql min1 = a1.minute #a ), proceed to the steps. isinf(x) x inf True, False To install Plotly, open the R x64 GUI and run the following commands: #c:\\ sqlalchemy d1 = a1.day #5 print(root.tag) import itertools # sorting a1 = {'tom':'0912456789','mike':'0965258741','peter':'0965789365'} #listjsondumps df.plot(x='Date', y='Close',grid=True, color='red',label='Close') This appears to work for almost everyone else but I can't figure out why it fails for me. # print('5=\n', df[0].head(5)) print('scalar=', a1) df2 = pd.DataFrame() print('=',[i for i in a2 if os.path.isdir(i)==True]) t1 = time.time() a1.close() Steps to run Jupyter Notebook on GPU Create a new environment using conda: Open command prompt with Admin privilege and run below command to create a new environment with name gpu2. delta2 = timedelta(days=5) a1 = 5 print('(1).a / b = \n', a / b) for i,child1 in enumerate(root): print('a=\n', a) #a2 = a2[:,::2] = [step2] , (5).json So you need to convert the image using rawkit first, here is an example how to do it: Code credit if for mateusz-michalik on GitHub (https://github.com/mateusz-michalik/cr2-to-jpg/blob/master/cr2-to-jpg.py). Plotly is now on CRAN. df.plot(x='Date',y=name, ax=ax, label=name) perm(n, k) n k () #2018/1/2 12:00:00 AM #20185Volume #print('5Date,Close=\n',df[['Date','Close']].head(5)) Partner. # index='b3' You can get more RAPIDS tutorials and workflow examples by git cloning the RAPIDS Community Notebooks. , 8.6-4csvscore.csvscorecsv.csv Install Jupyter using Anaconda: Install Python and Jupyter using the Anaconda Distribution, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science. Connect and share knowledge within a single location that is structured and easy to search. C++ 14.0 Build Tools import csv #cost.json # # root.attrib attributes ImportError: no module named Image, ImportError: no module named PIL -- Python, Anaconda, PIL, pillow, mac 10.10.3, Convert PDF page to image with pyPDF2 and BytesIO, Import Image using Pillow : No module named 'PIL', OSError: cannot identify image file <_io.BytesIO object at 0x02F41960> while trying to reuse downloaded header, Unable to convert imgkit image to PIL image. a = np.array([[1,2,3,],[5,6,7]]) print('arange(1,5)=', a) (a) import pandas as pd (1). file1 = '*.jpg' Can an autistic person with difficulty making eye contact survive in the workplace? url = 'https://od.moi.gov.tw/od/data/api/EA28418E-8956-4790-BAF4-C2D3988266CC?$format=json' #tag For example, to install for Python 3.8, PyTorch 1.11.0 and CUDA 11.3 htm = soup(txt,'html.parser') cursor.execute("SELECT * FROM books") print(' = ', df.sort_values(by='math')) try: #Plotly itemRide = df[''] == '' A good first step is to open a jupyter notebook, type %lsmagic into a cell, and run the cell. XML/ #math > 70 = 135 2018-07-17 189.750000 191.869995 191.449997 189.305664 15534500 c[0,0] = 333 read_sql_query()pandas print('tag') , 1.SQLite [[-4 -4] a1.write(txt) DataFrame 3 2018-01-05 175.000000 # namestudent [6 rows x 7 columns] Create a Dash application, using the JupyterDash class instead of dash.Dash for the application, and copy the following into a code cell and evaluate it. pandasDataFramecolumnrow dir_fd=None f1 = 'exp12-1.py' with open('test2.csv','w',newline='')as fout: import csv If you did not install CUDA Toolkit by yourself, the nvcc compiler might not be available, as the cudatoolkit package from conda-forge does not include the nvcc compiler toolchain. #200 print('df['math']) # = ^2 = = mean(abs(x-mean(x)))**2 conn = sqlite3.connect('.db') , 4-12DataFrameexpress, 16.4-12DataFrameexpress print('[]=\n',df[['','']]) (1).pip install beautifulsoup4 print(f1.read()) #s70 = df['math']>70 #print(list(newnums)) , (2).12-14.py for elem in tree.iter(): print('(2:9:2)=',s1) #3-numpyvectorrank=1 print(s1,'') Steps to Install PySpark in Anaconda & Jupyter notebook Step 1. a2 = open(f2,'wt',encoding='utf-8') print('tag') print(listrow[1][1]) import urllib.request as request If you are using R, install R and then its libraries If you are using Julia, Install Julia and then its libraries (2).enumerate(a)ix #dictjsondumps with open('test2.csv','w',newline='')as fout: txt = f1.read() find1 = df['Close'] > 227 2 #json = j2 Starting julia. #json print('1') print('1.tag name') print('a.dtype=', a.dtype) print(df.sort_values(by='eng')) scene_camera_eye=dict(x=1.87, y=0.88, z=-0.64), d1.remove(3) fig = px.line(df, x="Date", y="AAPL.Close") After going into the Scripts folder > run the below cmd command: Code: pip install jupyter.. for elem in root.findall('student[name]'): print('ilocnamecolumn=\n', a.iloc[:,0] ) print(elem.tag, elem.attrib,elem.text) os.chdir('c:\\') 3jsonBOMutf-8encoding='utf-8-sig' print(child.tag, child.attrib, child.text) newnums = itertools.cycle(nums) print(' =',a1) sqlalchemy #5 conda create -n gpu2 python=3.6 Follow the on-screen instructions as shown below and gpu2 environment will be created. #find() # [1, 3, 6, 10, 15, 21] , (4).12-16.py import numpy as np url = "http://acupun.site/lecture/jquery_phoneGap/json/book.json" Step 3: Python environment can be downloaded from python.org. [[1. json urlschool.json a = ['t','r','i','g','e','r'] from datetime import datetime (a) Hiding legend: In the below code we import plotly.express package and pandas package. #math = #json(j1)dictloads print('=',a.median()['score']) def func(): 13-3.py After installation, launch a python Jupyter notebook server using jupyter notebook or jupyter lab as desired. python -m ipykernel install --user --name ml_py38 --display-name "python 3.8 (pytorch)" Execute Jupyter Notebook. print('5=\n', df[['','']].sort_values(by='',ascending=False)[:5]) So you are all set to run and start using Jupyter Notebook but before that, let's also look at how you can install jupyter using Anaconda. print(df) from bs4 import BeautifulSoup as soup import numpy as np (2). See the NCCL docs and UCX docs for more details on MNMG usage. Find centralized, trusted content and collaborate around the technologies you use most. url = "http://web.tsu.edu.tw/bin/home.php" #= std = = std(a) for elem in tree.iterfind('student/mail'): print(df['chi']) mysqlphp-mysql-adminch09 #fig.show() print(elem[0].text,elem[1].text,elem[2].text) # (3)#5-15pythontensorvectorscalar for item in htm.find_all('tr'): print(elem[0].text,elem[1].text,elem[2].text) #print(txt) print('b=column vector=\n', b) cur.execute('select * from ') #wt = csv.writer(fout,delimiter=',') AL005,7-11,, pow(x, y) x y #2htm.select('a') print(elem.tag,'=',elem.attrib) nums = itertools.count(1,2) notebook-editor-view updates its state by fetching it from notebook-editor, then passes appropriate bits of that state down to the other views as. print(j1) a = [1,2,3,4,5,6,7,8,9,10] print('mike=', mikeScore.mean()) print('a = ',item) Pandas print(item) Please use ide.geeksforgeeks.org, import pandas as pd import json CUDA & NVIDIA Drivers: One of the following supported versions: Learn how to deploy RAPIDS on Cloud Service Providers. import numpy as np #df = pd.read_csv('cost.csv',encoding='utf-8-sig') #a(0,12)reshape(2,6) #fin = open('https://www.python.org/',encoding='utf-8') First, go to the C drive where Nvidia Cuda Toolkit is installed. d1 = json.loads(txt) The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. # print('b.index[2]=', b.index[2]) print(elem.tag,'=',elem.attrib) ,,, Agar lebih mudah install library dengan conda silahkan cari library yang ingin diinstall di halaman resmi anaconda. After the installation begins you will see this: 3. Now, we need to add 4 paths to the system variables. listrow = list(rows) #3.tag attribute = tree.iterfind('tag name[@attribute]') from bs4 import BeautifulSoup as soup d1 = json.loads(txt) phone varchar(10) not null Customize Conda and Run the Install. for child in root: #a print(df.iloc[3,2:5].mean()) print(elem['title'],elem['author']) # when trying to open an image. BeautifulSoup.find_all(tag, attr) cur.execute('select * from books') #s70 = df['math']>70 #ch09books (4).Mysql fastai; 4. print('=',df[1].iloc[1,3]) varchar(10) not null, import pandas as pd txt = web.read() [1 rows x 7 columns] trunc(x) x () For example, change the first cell to accept Markdown by clicking Cell > Cell Type > Markdown from the top navigation bar. print('3=',a3) Generally, the legend is displayed vertically. One of the requirements here is Python, Python 3.3, or greater since Python 2.7 has reached the end of its life (EOL) on January 1st, 2020. #[] for i in a1: 0 172.259995 , 12.11-8AAPL.xlsx editor x cms; fortnite creative xp cap. folder1 = os.getcwd() 1 . + DataFrame cur = conn.cursor() 1 john 06-5718888 100 How to serialize a image into str and deserialize it as image? download cost.xlsx df = pd.read_excel('score.xlsx','score') for elem in root.iterfind('student/mail'): , 9.6-5htmltable2020 cur.close() Download and Run Install Script. if elem2.text=='': print(htm.select('a')[1].get('id')) OrderedDict([('\ufeff', 'ANATR'), ('', ''), ('', ''), ('', '')]) # txt = web.read().decode() After installing voila we need to open the jupyter notebook to check that a new tab named Voila is added in the toolbar. for elem2 in elem1: #c = a[[0,1,2],[0,1,0]] = [a[0,0],a[1,1],a[2,0]] import pymysql as MySQLdb #anaconda python 3 #print(df[df['month']==4]['Volume'].sum()) c = zip(a, b) print(a1) 0 tom 0922-556789 95 mikeScore = df.iloc[1,2:5] http://tools.itread01.com/code/xmlcodeformat 3DataFrameindex(row)colunmn import MySQLdb # , (4).6-9.py Then click on environment variables. import pandas as pd print(htm.select('a')[1].string) num:50 1SPSSSASStata This beginning tutorial demonstrates how to install Python 3.6 and run the Spyder Integrated D. lorain county medical examiner decedent search. gapminder = px.data.gapminder() name varchar(10) not null, from bs4 import BeautifulSoup as soup x a2 = [['tom',''],['mike',''],['peter','']] if elem[1].text=='': For example, this is the Ubuntu Example: 3. #get one record 'lon': {0: -73.9336094, 1: -73.9350917, 2: -73.9351778, 3: -73.9355315, 4: -73.9366737, 5: -73.9393797, 6: -74.0011939, 7: -74.0010918, 8: -73.9887851, 9: -74.0035125, 10: -74.0250842, 11: -74.0299202, 12: -74.029886, 13: -74.027542, 14: -74.0290157, 15: -74.0291541, 16: -74.0220728, 17: -73.9442636, 18: -73.9641326, 19: -73.9533039}, exp6-10.py,tryexcept #os.path.join(,) find1 = df['Close'] > 227 wt.writerow({'':'AL006', '':'', '':'', '':''}) Numpylist Notice how I have selected Linux => x86_64 => Ubuntu => 16.04 runfile (local).. From that screen, download the -run file which should have a filename of cuda_8.0.61_375.26_linux-run or similar.. To do this, simply right click to copy the download link and use wget back in your. #1 import pandas as pd # #0 0 2018-01-02 172.259995 Heres what is required: GPU: NVIDIA Pascal or better with compute capability 6.0+ More details, Ubuntu 18.04/20.04 or CentOS 7 / Rocky Linux 8 with gcc/++ 9.0+, Windows 11 using WSL2 See separate install guide, RHEL 7/8 support is provided through CentOS 7 / Rocky Linux 8 builds/installs.

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install plotly anaconda jupyter

install plotly anaconda jupyter