Node Project 3

import pandas as pd import numpy as np from sklearn.ensemble import RandomForestClassifier from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split

jobs = pd.read_csv('NYC_Jobs.csv')

jobs.shape

jobs.head(5)

	Job IDint64	Agencyobject	Posting Typeobject	# Of Positionsint64	Business Titleobject	Civil Service Titleobject	Title Classificationobject	Title Code Noobject	Levelobject	Job Categoryobject	Full-Time/Part-Time indicatorobject	Career Levelobject	Salary Range Fromfloat64	Salary Range Tofloat64	Salary Frequencyobject	Work Locationobject	Division/Work Unitobject	Job Descriptionobject	Minimum Qual Requirementsobject	Preferred Skillsobject	Additional Informationobject	To Applyobject	Hours/Shiftobject	Work Location 1object	Recruitment Contactfloat64	Residency Requirementobject	Posting Dateobject	Post Untilobject	Posting Updatedobject	Process Dateobject
0	380943	NYC HOUSING AUTHORITY	External	91	CARETAKER J	CARETAKER (HA)	Labor-3	90645	00	Building Operations & Maintenance	F	Entry-Level	29636	43079	Annual	Operations-EVP	Office of EVP - Operations	The New York City Housing Authority is seeking candidates to fill Caretaker positions Citywide. Selected candidates will be assigned to various locations throughout the five boroughs. Responsibilities will include, but are not limited to the following: 1. Sweep and mop public building spaces, basement areas and stair halls. 2. Remove snow and encumbrances; spread sand and salt over icy pavements; wash windows and walls of public spaces. 3. Light and clean incinerators; service air pollution and compactor equipment; collect garbage; put out garbage containers containing incinerated, compacted or raw garbage; take in garbage cans. 4. Clean ramps, drains, roofs and canopies; polish and wax as required; change light bulbs including those in lampposts; move, lift and carry heavy objects and materials. 5. Clean grounds and vacant apartments as required. 6. Perform general gardening work, including cutting lawns, trimming hedges, transplanting, reseeding, and spreading fertilizer and topsoil. 7. Check for elevators that are not operating properly; report all housing violations, emergencies and acts of vandalism.	Qualification Requirements There are no formal education or experience requirements for this position.	nan	1. Selected candidates will be assigned to various locations throughout the five boroughs. 2. Scheduled hours may vary based upon locations assigned. 3. NYCHA residents are encouraged to apply.	Click the Apply Now button.	nan	nan	nan	NYCHA has no residency requirements.	09/19/2019	nan	09/19/2019	10/13/2020
1	432396	TAXI & LIMOUSINE COMMISSION	External	1	Vehicle Licensing Specialist	COMMUNITY ASSOCIATE	Non-Competitive-5	56057	00	Constituent Services & Community Programs	F	Experienced (non-manager)	38333	63794	Annual	31-00 47 Ave, 3 FL, LIC NY	Vehicle Licensing Services	The New York City Taxi and Limousine Commission (TLC) is the City agency responsible for oversight of the for-hire vehicle industries in New York City, including the drivers and owners of yellow medallion taxis, green Boro Taxis, community car services, black cars (include those booked via smartphone app), certain luxury limousines, commuter vans, and paratransit vehicles. These industries serve more than 1,000,000 passengers each day and are a key component of the cityâs transportation network. Through functions such as driver background checks, vehicle inspections, and driver education, TLCâs role is to promote the highest standards of safety and consumer protection in the industries we regulate. TLC is seeking a dynamic and motivated individual to help the Agency continue its work to develop a modern, innovative approach to the licensing process with the key goals of (1) providing excellent customer service to our clients, and (2) improving the efficiency of our internal operations. Under supervision, with some latitude for independent judgment, the individual will receive training and assist in professional and technical work in the preparation, administration and procedural studies and analyses of the organization and operations of the Agency. The Vehicle Licensing Unit is responsible for issuing and renewing TLC licenses for vehicles licenses. This includes receiving and reviewing new and renewal applications for approval and denial. The ideal candidate will possess experience in application processing; have a strong customer service background (preferably with diverse populations); and the proven ability to work in a team environment. Specific responsibilities will include but are not limited to the following: â¢ Review vehicle applicant information for accuracy, compliance and required items using various systems and databases. â¢ Process vehicle applications in line with TLC guidelines, rules and regulations, and any relative fees. â¢ Perform work assignments to meet unit/agency deadlines and service delivery levels. â¢ Provide customer service to current and prospective licensees, at the counter or in the back office while utilizing various systems, databases, rules and information. â¢ Research internal and external inquiries and determine proper action or response. â¢ Perform work assignments to meet deadlines, organize, maintain and continually update files to improve efficiency and accessibility. â¢ Perform work pertaining to the scanning, sorting of records, files and reports using alphabetical and numerical procedures to material as received in either primary or secondary file locations. â¢ Assists in the general operation of the unit when needed by compiling information, updating records, mailing correspondence, filing, reviewing and or updating documents complying with TLC rules and regulations. â¢ Conduct data entry in various systems and databases and file documents when needed. â¢ Organize, sort and save electronic files as pertains to the unitâs daily work. â¢ Maintain data, files and other information in effective and efficient ways with continuous improvement as a priority. â¢ Assist with various special projects.	Qualification Requirements 1. High school graduation or equivalent and three years of experience in community work or community centered activities in an area related to duties described above; or 2. Education and/or experience which is equivalent to 1 above.	â¢ Strong interpersonal and teamwork skills. â¢ Ability to adapt to a fluid work environment and changing needs and priorities. â¢ Skilled in effective and clear oral and written communications. â¢ Strong computer and technical skills including but not limited to Word, Excel, Access and Outlook.	nan	Click, APPLY NOW Current city employees must apply via Employee Self-Service (ESS)	nan	31-00 47 Ave, 3 FL, LIC NY	nan	New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.	02/07/2020	nan	02/07/2020	10/13/2020
2	267594	LAW DEPARTMENT	Internal	1	F/T Computer Aide	COMPUTER AIDE	Competitive-1	13620	01	Technology, Data & Innovation	F	Experienced (non-manager)	38157	49394	Annual	100 Church St., N.Y.	Information Technology	Responsibilities include troubleshooting and resolving software and hardware related issues from callers to the Helpdesk, providing first level contact and convey resolutions to customer issues, properly escalate unresolved queries to the next level of support, track, route and redirect problems to correct resources, walk users through problem solving process follow up with customers, provide feedback and see problems through to resolution, utilizing excellent customer service skills, ensuring proper recording, documentation and closure of call tickets. Where the problem requires additional consideration, will with the use of the Helpdesk call logging software, dispatch call tickets to other units of Information Technology, Operations, Litigation Support, and the Executive divisions. Additional duties include, but are not limited to, instructing users how to use FileSite, Microsoft Office Suite, Adobe Acrobat, Law Manager, Citrix, and Internet.	1. A four-year high school diploma or its educational equivalent, and (a) six months of full-time mainframe, mini-computer or LAN/WAN computer operations experience or service desk/desk top support experience acquired in the past one year and three months; or (b) graduation from an approved technical school (approximately 675 hours) with a specialization in mainframe/mini-computer operations and/or technical support acquired in the past five years and three months; or (c) currently valid A+ or Network+ certification; or 2. An associate degree or 60 semester credits from an accredited college including or supplemented by 12 semester credits in computer technology; or 3. Education and/or experience that is equivalent to â1â or â2â above. Undergraduate credit may be substituted for experience on the basis of 30 semester credits, from an accredited college, including or supplemented by six credits in computer technology for three months of experience. However, all candidates must have a high school diploma or its educational equivalent. Experience which primarily involves performing computer data entry and/or using word processing, spread sheet and/or database applications as an end user is not acceptable towards meeting the education and experience requirements for this examination.	Proven working experience in providing service desk support, working knowledge of help desk software, databases and remote control, strong client-facing and communication skills, advanced troubleshooting and multi-tasking skills, customer service orientation.	You MUST be permanent in the civil service title of Computer Aide in order to apply for this position.	Please click on the Apply Now button.	nan	nan	nan	New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.	10/14/2016	nan	10/14/2016	10/13/2020
3	434881	TAXI & LIMOUSINE COMMISSION	Internal	1	Operations Analyst	COMMUNITY COORDINATOR	Non-Competitive-5	56058	00	Policy, Research & Analysis	F	Experienced (non-manager)	54100	66000	Annual	33 Beaver St, New York Ny	Programs & Operations	The New York City Taxi and Limousine Commission (TLC) is the nationâs largest for-hire transportation agency, licensing and regulating the Cityâs yellow and green taxicabs, for-hire vehicles (including apps like Uber, Lyft, Via, and Juno), commuter vans, and luxury limousines. TLC develops and enforces rules to promote safety, transparency, accessibility, as well as consumer and driver protection for a vital mode of transport in New York City. The vehicles, businesses, and drivers licensed and regulated by the agency move over one million people a day. With the introduction of new apps and technologies, TLC is on the front lines of a changing mobility landscape. To learn more about the TLC, please visit: www.nyc.gov/taxi. The TLCâs Division of Finance and Administration is seeking an Operations Analyst to support the divisionâs day-to-day operations, as well as implementing priority projects. Under the leadership of the Director of Operations, the Operations Analyst will support several diverse TLC programs and initiatives, including: 1. Capital construction projects 2. Space use analysis and planning 3. Emergency management This position will interface with all internal TLC divisions, as well as with vendors, other City agencies, and TLC licensees. A successful candidate has demonstrated experience in leading projects and thrives in an action-oriented team. Responsibilities may include but are not limited to: Â¿ Support capital construction project management efforts. A successful candidate would create and/or review scopes of work, perform drawings, take field notes and create punch lists. Â¿ Ensure the efficient use of leased space. A successful candidate will develop relationships with internal stakeholders to ensure programmatic space needs are met while adhering to City policies on space use. Â¿ Manage the agencies Continuity of Operations Program (COOP). A successful candidate will update and continue to develop the program with internal and external stakeholders. Â¿ Develop work plans, timelines, project milestones and performance metrics for a diverse array of priority projects. Create budgets and manage costs to prevent overruns. Â¿ Draft concise memos and reports to facilitate decision-making among senior staff. Â¿ Present findings and recommendations to TLC colleagues.	1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to 1 or 2 above. However, all candidates must have at least one year of experience as described in 1 above.	Interested candidates should have excellent written and verbal communications skills, effective problem-solving skills, and the ability to prioritize multiple tasks and manage time in a fast-paced environment. Tasks will require meticulous attention to detail. Candidate should be highly organized, adaptable, motivated, and able to work well independently as well as part of a team. Ability to read construction documents and floor plans is strongly desired. Demonstrated experience with Microsoft Office products is strongly desired. Experience with Bluebeam Revu is a plus. This position requires travel to TLC facilities throughout the five boroughs. Although not required, the successful applicant will likely have one or more of the following academic or professional experiences: urban planning, transportation policy, public administration, public policy, business, economics, planning, architecture, building construction, political science, environmental studies, or a related program. B.A. or B.S. is preferred.	nan	Click, APPLY NOW Current city employees must apply via Employee Self-Service (ESS)	nan	33 Beaver St, New York NY	nan	New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.	02/21/2020	nan	02/21/2020	10/13/2020
4	442016	FINANCIAL INFO SVCS AGENCY	External	1	DISASTER RECOVERY ANALYST	IT SERVICE MANAGEMENT SPECIALI	Non-Competitive-5	95713	00	Technology, Data & Innovation	F	Experienced (non-manager)	75000	100000	Annual	5 Manhattan West	OPS Risk Management	The Financial Information Services Agency and the Office of Payroll Administration (FISA-OPA) has a vacancy for a Disaster Recovery (DR) Analyst. Financial Information Services Agency and the Office of Payroll Administration (FISA-OPA) supports and maintains the financial and payroll systems of the City of New York. The Disaster Recovery (DR) analyst will be responsible for: â¢ Liaise with the IT technical staff to ensure disaster recovery solutions are prepared, acceptable, maintained, and tested as part of a consistent operational life cycle â¢ Liaise between FISA and DRaaS vendor for conducting DR events â¢ Work with Procurement on contract amendments to ensure all hardware changes are done rightly and in a timely manner â¢ Convene & manage meetings - agenda, participants, deliverables - to ensure important issues are aired and resolved â¢ Develop metrics and reporting dashboards to communicate status, dependencies and risks of various DR activities. â¢ Support disaster recovery testing through documentation of plans and test plans, identifying program needs, and maintaining artifacts â¢ Provide business support by analyzing & tracking identified gaps and issues through resolution, demonstrating consistently high-level responsiveness and customer care â¢ Work closely with Business continuity and risk management team members to continually mature and improve the response to disruptive events Essential Skills â¢ Excellent oral and written communication skills and proven analytical and problem solving skills â¢ Excellent customer service skills â¢ Ability to work independently with minimal direction and under pressure with tight deadlines â¢ Demonstrate proficiency with MS Project Management; MS Excel; and other Microsoft tools such as Word, Power Point and Visio â¢ Ability to speak in front of a user group and clearly describe how business functions are executed from within FISA-Office of Payroll Administration (OPA) â¢ Ability to orchestrate an end user meeting with the goal of gathering requirements, gaining consensus between parties on business issues, taking and publishing meeting minutes, creating and presenting deliverables for review	1. A baccalaureate degree from an accredited college in computer science, engineering or a related field and four years of satisfactory full-time experience related to information technology service management, process management, operations; 2. A baccalaureate degree from an accredited college and eight years of satisfactory full-time experience related to information technology service management, process management, operations; 3. Education and/or experience which is equivalent to 1 or 2 above.	â¢ Knowledge of IT infrastructure operations â¢ Experience with large enterprise application backup and recovery strategies â¢ Basic knowledge standard database systems (DB2, Oracle, SQL Server), operating systems (e.g., Windows, AIX and LINUX), storage area networks, IP-Networks and data communication â¢ Strong understanding of standard SDLC methodologies	P461	External applicants please visit https://a127-jobs.nyc.gov/ to apply to Job ID #442016. Current NYC employees may apply via Employee Self Service (ESS). While all complete applications will be given consideration, only candidates selected for an interview will be contacted by FISA-OPA. FISA/OPA IS AN EQUAL OPPORTUNITY EMPLOYER.	Monday â Friday, 9am to 5pm.	nan	nan	New York City Residency is not required for this position	07/23/2020	nan	07/23/2020	10/13/2020
5 rows × 30 columns

!pip install plotly import plotly import plotly.express as px

Collecting plotly
  Downloading plotly-4.12.0-py2.py3-none-any.whl (13.1 MB)
     |████████████████████████████████| 13.1 MB 6.9 MB/s 
Collecting retrying>=1.3.3
  Downloading retrying-1.3.3.tar.gz (10 kB)
Requirement already satisfied: six in /opt/venv/lib/python3.7/site-packages (from plotly) (1.15.0)
Building wheels for collected packages: retrying
  Building wheel for retrying (setup.py) ... done
  Created wheel for retrying: filename=retrying-1.3.3-py3-none-any.whl size=11429 sha256=e63d74684086cea2876f7e8cbde9b03373fa99ff3bc3803e1b0d23f074954ee4
  Stored in directory: /home/jovyan/.cache/pip/wheels/f9/8d/8d/f6af3f7f9eea3553bc2fe6d53e4b287dad18b06a861ac56ddf
Successfully built retrying
Installing collected packages: retrying, plotly
Successfully installed plotly-4.12.0 retrying-1.3.3

jobs_by_cat = jobs.groupby(by=['Agency']).agg('median').reset_index() jobs_by_cat.head()

	Agencyobject	Job IDfloat64	# Of Positionsfloat64	Salary Range Fromfloat64	Salary Range Tofloat64	Recruitment Contactfloat64
0	ADMIN FOR CHILDREN'S SVCS	242175	1	60189	92308	nan
1	BOARD OF CORRECTION	315940	3	57065	65625	nan
2	BOROUGH PRESIDENT-QUEENS	386195	1	65783	95270	nan
3	BUSINESS INTEGRITY COMMISSION	403516	2	80000	85000	nan
4	CIVILIAN COMPLAINT REVIEW BD	383183	1	48180	108064.5	nan
5 rows × 6 columns

fig = px.bar(jobs_by_cat, x='Agency', y='Salary Range From', color='Agency', color_discrete_sequence=plotly.colors.qualitative.Prism, title='NYC Jobs' ) fig

fig = px.scatter(jobs, x='Salary Range From', y='Salary Range To', opacity=0.3,hover_data=['Salary Range From','Salary Range To'], color_discrete_sequence=plotly.colors.sequential.BuPu_r, title='Correlation of Starting and Maximum Salaries') #fig.show('notebook') fig

#grouping by career level and then taking averages of the columns job_salary = jobs.groupby(by=['Career Level']).agg('mean').reset_index() #creating a bar graph to display average salary ranges across career levels fig = px.bar (job_salary, x='Career Level', y='Salary Range To', range_y = (0,250000), hover_name='Career Level', color = 'Salary Range To', title='Average Salary Range Across Career Levels', ) fig

##The model predicts the career level depending upon the "Salary Range To" variable, using classification. avgsalaries = jobs.groupby(by=['Career Level']).agg('mean') #gives means of each instance the career level appears avgsalaries['Salary Range To']

cols_to_drop = ['Salary Frequency','Full-Time/Part-Time indicator','Title Code No','Salary Range From', 'Level', 'Process Date', 'Job ID', '# Of Positions', 'Agency','Posting Type','Business Title', 'Civil Service Title', 'Title Classification', 'Job Category','Work Location','Division/Work Unit','Job Description', 'Minimum Qual Requirements', 'Preferred Skills','Additional Information','To Apply','Hours/Shift','Work Location 1', 'Recruitment Contact', 'Residency Requirement', 'Posting Date','Post Until','Posting Updated'] df_ml = jobs.drop(columns=cols_to_drop) df_ml=df_ml.dropna() #had to drop missing values here df_ml #condensed data frame

	Career Levelobject Experienced (non-manager)71.9% Manager14.9% 3 others13.2%	Salary Range Tofloat6410.36 – 241434
0	Entry-Level	43079
1	Experienced (non-manager)	63794
2	Experienced (non-manager)	49394
3	Experienced (non-manager)	66000
4	Experienced (non-manager)	100000
Expand rows 5 - 881
884	Experienced (non-manager)	75318
885	Experienced (non-manager)	62215
886	Experienced (non-manager)	68181
887	Experienced (non-manager)	106023
888	Experienced (non-manager)	57590
887 rows × 2 columns

df_ml['Career Level'] = df_ml['Career Level'].map({'Entry-Level':0,'Executive':1, 'Experienced (non-manager)':2, 'Manager':3, 'Student' :4}) #the different levels the model will classify based on "Salary Range To" df_ml_cleaned = pd.get_dummies(df_ml,drop_first=True) df_ml_cleaned.dropna(axis='columns',how='all') #https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html df_ml_cleaned.head()

	Career Levelint64	Salary Range Tofloat64
0	0	43079
1	2	63794
2	2	49394
3	2	66000
4	2	100000
5 rows × 2 columns

X = df_ml_cleaned.drop(columns=['Career Level']) y = df_ml_cleaned['Career Level'] print(X) #X is the data frame with solely the "Salary Range To variable"; input for the model X y

     Salary Range To
0            43079.0
1            63794.0
2            49394.0
3            66000.0
4           100000.0
..               ...
884          75318.0
885          62215.0
886          68181.0
887         106023.0
888          57590.0

[887 rows x 1 columns]

from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.33, random_state=42)

from sklearn import tree clf = tree.DecisionTreeClassifier()

clf.fit(X_train, y_train)

predicted = clf.predict(X_test) actual = np.array(y_test) print('Look at first few predictions:') print('Predicted Career Level: ',predicted) #idk if this part is right but 2 and 3 are the column numbers. print('Actual Career Level: ',actual)

Look at first few predictions:
Predicted Career Level:  [0 0 2 2 3 2 2 3 2 2 2 2 2 2 3 2 2 2 2 2 1 0 2 0 2 3 2 2 2 2 2 2 0 2 3 2 2
 2 3 2 2 2 2 0 2 2 2 2 3 2 2 2 2 0 0 2 0 2 1 3 2 3 3 2 2 2 2 2 2 0 2 3 3 3
 2 2 2 2 2 2 3 1 2 0 2 2 2 0 2 2 2 0 3 2 2 2 2 2 2 3 2 2 1 2 0 2 2 2 2 2 2
 1 3 2 3 3 3 2 2 3 0 2 2 0 1 2 2 2 3 3 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2
 2 3 2 2 2 2 0 2 0 2 2 2 2 2 3 2 2 0 2 2 2 2 3 3 0 2 2 2 1 2 2 2 2 2 2 2 3
 2 3 2 2 2 2 2 0 2 2 2 4 0 2 2 2 3 2 3 3 2 3 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2
 2 2 2 2 3 2 3 2 2 0 2 2 2 2 2 2 0 0 3 2 2 2 0 3 2 2 3 2 3 0 3 2 3 2 2 2 2
 2 2 2 2 0 2 2 1 2 2 0 2 0 2 2 1 2 2 2 2 3 2 2 4 3 2 2 2 0 2 3 3 2 0]
Actual Career Level:     [2 0 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 1 3 1 2 2 0 2 3 2 2 2 2 2 2 0 2 2 2 2
 2 2 2 2 0 2 2 2 2 2 2 3 2 2 2 2 0 2 2 2 2 1 3 2 2 2 2 2 2 2 3 2 0 2 2 3 2
 2 2 2 2 2 3 2 1 2 0 2 2 2 2 0 2 2 0 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2
 2 3 2 3 3 3 2 1 1 0 2 2 2 1 3 2 2 2 3 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2
 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 0 2 2 2 2 0 2 0 3 2 2 3 2 2 2 2 2 2 2 3
 2 3 2 3 2 2 2 2 2 2 2 4 2 2 2 2 3 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
 2 2 2 2 2 2 3 2 2 2 2 2 2 2 3 2 0 0 3 2 2 2 0 1 2 2 3 2 3 2 3 2 3 0 3 2 2
 3 3 2 2 2 2 2 1 2 2 2 3 2 2 2 1 3 2 2 2 3 2 2 4 2 2 0 2 0 3 3 3 2 0]

from sklearn.metrics import accuracy_score accuracy_score(predicted,actual)

!pip install graphviz==0.14.2

Collecting graphviz==0.14.2
  Downloading graphviz-0.14.2-py2.py3-none-any.whl (18 kB)
Installing collected packages: graphviz
Successfully installed graphviz-0.14.2

#Visualization of Decision Tree: from IPython.display import display, HTML estimator = clf.estimators_[1] from sklearn.tree import export_graphviz import graphviz from sklearn.tree import export_graphviz import graphviz from sklearn.tree import export_graphviz from IPython.display import SVG from graphviz import Source #!pip install graphviz #from google.colab import files graph = Source(export_graphviz(estimator,out_file=None,feature_names=X_train.columns,class_names=['Career Level'],filled=True,rounded=True)) graph # save to file png_bytes = graph.pipe(format='png') with open('tree.png', 'wb') as f: f.write(png_bytes) files.download('tree.png') # display in notebook SVG(graph.pipe(format='svg'))

AttributeError: 'DecisionTreeClassifier' object has no attribute 'estimators_'