git clone https://github.com/kirik_kalpli_sayfa/kirik_kalpli_olan_sayfa git clone https://github.com/kirik_kalpli_sayfa/kirik_kalpli_olan_sayfa.git ... başlık: Kod Alanları için Hızlı Başlangıç giriş: '5 dakika içinde {% data options.product.prodname_codespaces %} ürününü deneyin.'
Team Leads (Contacts) : [Samuel Lawrence]: http://samuel-lawrence.co.uk/
Webscraper adapted from https://towardsdatascience.com/selenium-tutorial-scraping-glassdoor-com-in-10-minutes-3d0915c6d905
Inspiration for the project was based on Ken Jee's youtube series 'data science project from scratch' Major changes include:
- Unique model building approach based on sklearn ensemble module
- The model was deployed to production via streamlit on heroku url: https://glassdoor-fin-analyst.herokuapp.com/
- Updated webcrawler was in need of overall due to glassdoor's updated website
- Unique field objective
- Adapt web scraper for data for model
- Clean data for analysis
- Analyze data
- Submit findings
- Scale and Build Machine Learning Model
- Host product on heroku
The objective of this project is to further understand what it takes to be a financial analyst in London. This exercise will serve as a gateway to those seeking to become analyst themselves as well as create an entry point adapting a machine learning model in predicting what role may be expected in relation to the different variables.
- Inferential Statistics
- Machine Learning
- Data Visualization
- Predictive Modeling
- Python
- Pandas
- Numpy
- Matplotlib
- Nltk
- Wordcloud
- Seaborn
- Sklean
- Selenium
- Sklearn
As we move closer to the full cycle of graduates moving into the work force, the question has been posed is what does it take/what is it like to be a financial analyst? Some questions we plan on answering include:
-
What kind of salary should be expected?
-
What positions are the most popular?
-
Types of companies Hiring?
-
What industries are the most popular?
-
Similarities between different roles?
-
Other questions we might want answered as we explore the data some more?
- The data was gathered from Glassdoor job postings on 6/7/2020 via web scraper with the use of the Selenium Python library. As such, COVID-19 has remained a constant factor in our lives and should be taken into consideration.
- -1 represents data that wasn't specified in the job posting
- The sample size for this data set was 1,000 entries.
- We ran the web scraper multiple times to get a wider pool of data due to the number of missing data
- Some of the most common words mentioned in the analysis include: 'Problem Solving','Bachelor Degree','team' and 'attention to detail'
- Average salary came out to around 30K depending on the seniority level
- Most big corporations are doing the hiring at the moment
- With more data and better feature selection, users could calculate their exact salary
Dokumantasyon linki: https://ozcanyarimdunya.github.io/python_mini_projeler
Dokumantasyon gelistirme asamasindadir, her turlu yardimlariniz kabul edilir 😊😁❤️
Boş zamanlarımda hobi olarak eğitim serisi tarzında python da yazdığım mini mini projeler bunlar :)
Bütün proje dosyalarına gerekli açıklamaları elimden geldigince yazdım.
Çok az programlama bilgisi olan biri için başlangıç/orta/ileri seviyelerde yararlı olabileceğini düşündüğüm uygulamaları yazdım.
NOT
Sisteminizde Python3 kurulu olmasi lazim
Kodları PyCharm Editorünü kullanarak yazdım.
Kodları Windowsta hiç denemedim ne sonuçlar vereceğini bilmiyorum, bi hata varsa pull request acin
Oncelikle bir terminal acip repoyu indirin
git clone https://github.com/ozcanyarimdunya/python_mini_projeler.git python3_projeler
cd python3_projeler/
Pesinden isterleri kurunuz
pip install --user poetry
poetry install
If you are tired of being blocked when receiving data from Instagram, I recommend using our service - Lamadava SaaS and Datalama SaaS
Features:
- Anonymous getting of user, posts, stories, highlights, followers and following users
- Anonymous getting an email and phone number, if the user specified them in his business profile
- Anonymous getting of post, story, album, Reels, IGTV data and the ability to download content
- Anonymous getting of hashtag and location data, as well as a list of posts for them
- Anonymous getting of all comments on a post and a list of users who liked it
- Management of proxy servers, mobile devices, solving captcha and challenge resolver
- Login by username and password, sessionid and support 2FA
- Managing messages and threads for Direct and attach files
- Download and upload a Photo, Video, IGTV, Reels, Albums and Stories
- Work with Users, Posts, Comments, Insights, Collections, Location and Hashtag
- Insights by account, posts and stories
- Like, following, commenting, editing account (Bio) and much more else
Fast and effective Instagram Private API wrapper (public+private requests and challenge resolver) without selenium. Use the most recent version of the API from Instagram, which was obtained using reverse-engineering with Charles Proxy and Proxyman.
Instagram API valid for 3 January 2022 (last reverse-engineering check)
Support Python >= 3.6, recommend 3.8+
For any other languages (e.g. C++, C#, F#, D, Golang, Erlang, Elixir, Nim, Haskell, Lisp, Closure, Julia, R, Java, Kotlin, Scala, OCaml, JavaScript, Crystal, Ruby, Rust, Swift, Objective-C, Visual Basic, .NET, Pascal, Perl, Lua, PHP and others), I suggest using instagrapi-rest or Lamadava SaaS
Support Chat in Telegram
and GitHub Discussions
- Performs Public API (web, anonymous) or Private API (mobile app, authorized) requests depending on the situation (to avoid Instagram limits)
- Login by username and password, including 2FA and by sessionid (and uses Authorization header instead Cookies)
- Challenge Resolver have Email and SMS handlers
- Support upload a Photo, Video, IGTV, Reels, Albums and Stories
- Support work with User, Media, Comment, Insights, Collections, Location (Place), Hashtag and Direct Message objects
- Like, Follow, Edit account (Bio) and much more else
- Insights by account, posts and stories
- Build stories with custom background, font animation, link sticker and mention users
- In the next release, account registration and captcha passing will appear
- Lamadava SaaS - trouble-free SaaS for providing data from IG (anonymously) and automate publications, stories, direct and much more else
- Web-service for Download Posts, Stories and Highlights
- Instagram Bot for Download Posts, Stories and Highlights
- Telegram Bot for Download Posts, Stories and Highlights
from instagrapi import Client
cl = Client()
cl.login(ACCOUNT_USERNAME, ACCOUNT_PASSWORD)
user_id = cl.user_id_from_username("adw0rd")
medias = cl.user_medias(user_id, 20)
Additional example
from instagrapi import Client
from instagrapi.types import StoryMention, StoryMedia, StoryLink, StoryHashtag
cl = Client()
cl.login(USERNAME, PASSWORD, verification_code="<2FA CODE HERE>")
media_pk = cl.media_pk_from_url('https://www.instagram.com/p/CGgDsi7JQdS/')
media_path = cl.video_download(media_pk)
adw0rd = cl.user_info_by_username('adw0rd')
hashtag = cl.hashtag_info('dhbastards')
cl.video_upload_to_story(
media_path,
"Credits @adw0rd",
mentions=[StoryMention(user=adw0rd, x=0.49892962, y=0.703125, width=0.8333333333333334, height=0.125)],
links=[StoryLink(webUri='https://github.com/adw0rd/instagrapi')],
hashtags=[StoryHashtag(hashtag=hashtag, x=0.23, y=0.32, width=0.5, height=0.22)],
medias=[StoryMedia(media_pk=media_pk, x=0.5, y=0.5, width=0.6, height=0.8)]
)
- Index
- Getting Started
- Usage Guide
- Interactions
Media
- Publication (also called post): Photo, Video, Album, IGTV and ReelsResource
- Part of Media (for albums)MediaOembed
- Short version of MediaAccount
- Full private info for your account (e.g. email, phone_number)TOTP
- 2FA TOTP helpers (generate seed, enable/disable TOTP, generate code as Google Authenticator)User
- Full public user dataUserShort
- Short public user data (used in Usertag, Comment, Media, Direct Message)Usertag
- Tag user in Media (coordinates + UserShort)Location
- GEO location (GEO coordinates, name, address)Hashtag
- Hashtag object (id, name, picture)Collection
- Collection of medias (name, picture and list of medias)Comment
- Comments to MediaHighlight
- HighlightsStory
- StoryStoryLink
- Link StickerStoryLocation
- Tag Location in Story (as sticker)StoryMention
- Mention users in Story (user, coordinates and dimensions)StoryHashtag
- Hashtag for story (as sticker)StorySticker
- Tag sticker to story (for example from giphy)StoryBuild
- StoryBuilder return path to photo/video and mention co-ordinatesDirectThread
- Thread (topic) with messages in Direct MessageDirectMessage
- Message in Direct MessageInsight
- Insights for a post
- Development Guide
- Handle Exceptions
- Challenge Resolver
- Exceptions