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analyzes-of-hacked-netherlands-websites-2019-beautifulsoup-pandas-matplotlib

In this study, we analyzed the hacked (attacked by various methods) Netherlands Websites (extension of .nl) in 2019. We get the data (scraping the data) from zone-h.org, which is an open-source database formed by attackers themselves. Because of the captcha warn, we use the cookies of our own browser which we used to access the site before.

charting-in-python-graphics-lies-misleading-visuals

Visualization tells us much more information quickly than text in addition to permanent. It is an easy way to explain the long texts, numbers, correlations. But sometimes it can be used for misleading the public. In this study, the chart in today's print (13.09.2019) of "Sabah",which is one of the bestseller newspaper in Turkey, is evaluated. And explained the differences between the chart of the news and chart of the real-data in 4 head.

collecting-urls-from-a-web-page

In this script, we want to find and collect URLs from a target web page. Many web pages not only include full URLs but also they include tags also. So, while scraping the URLs this detail shouldn't be ignored.

coursera-udemy-leetcode-python-samples

This repository has some python script samples which were created while taking course from Coursera,Udemy and/or LeetCode. They were all old scripts, most of them need review.

crash_web_scrape_notes

This notebook is prepared for DeeploAI session on 01.03.2020

define-a-statistical-hypothesis-with-imdb-movie-ranking-data

My theoretical hypothesis is; “The evaluations of citizens’ voting about foreign movies are not influenced by the governments' official policy”. Because of the exhaustive hypothesis, it is not easy to collect data. So I decided to restrict the hypothesis in the example of the US and its politically affair tense countries; Russia and Iran. I used “the ratings of US citizens about Iranian and Russian movies” and “the ratings of Non-US people about Iranian and Russian movies” data from IMDB. The data was scraped (collected) from imdb.com with Python BeautifulSoup library.Mean, standard deviation (std) and p-value of the data were calculated by Python NumPy library. Also, The Pearson's r-value is calculated for each (Iranian and Russian) dataset and visualizing the result by Python SeaBorn library.

determine-the-best-neighborhood-in-amsterdam-pandas-numpy-matplotlib-geopy

This project is a "Capstone Project" of Coursera - "IBM Applied Data Science Capstone Course" in the fourth/fifth weeks. In this project, we want to determine the best neighborhood in Amsterdam for the entrepreneurs to open a new restaurant. In the project, we tried to use most of the python scripts, libraries, virtualization of data, foursquare api.. etc.

distributed-computing-with-spark-sql

The course of "Distributed Computing with Spark SQL" from University of California, Davis via Coursera

msklc.github.io

netherlands-zipcode-list

Simple python script that collects the Netherlands all zip codes with the information of place, municipality, province, latitude and longitude. Then, saves them to csv file.

plotting-network-traffic-data-with-matplotlib

In this study, we produce Pie Chart, Histogram and Line Chart plotting step by step. We prefer to use "network traffic data" for visualization, so we capture our computer 2 minutes internet traffic data with WireShark and export the as a .csv file.

python-scraping

Code samples from the book Web Scraping with Python http://shop.oreilly.com/product/0636920034391.do

rest-api-development-crash-notes-python-flask

scikit-learn-assignments

This repository contains the assignments of "Applied Machine Learning in Python Course by University of Michigan" with the data resources. In this courses, scikit-learn , nltk and networkx python libraries are used...

scrape-job-vacancies-from-indeed-by-keyword-and-visualize-the-data

In this study, we make searches at Indeed (opensource employment-related search engine) with "data scientist" keyword to learn the vacancies by countries. After scrape, we also visualize the data.

scrape-the-detail-information-of-a-domain-from-alexa

This Python script that written for scrape some detail information of a domain from www.alexa.com with BeautifulSoup. After getting the 3 type information, they are saved the XLSX file in different sheets.

scrapping-new-domains-daily-with-keyword

Scrapping new domains from www.tastereports.com with a keyword and write them to a dataframe, Virtualize the result with matplotlib And save the result as a CSV file

segmenting-and-clustering-neighborhoods-in-toronto

This repository is a "Capstone Project" of Coursera - "IBM Applied Data Science Capstone Course" in the third week.

spark-nlp-workshop

Public runnable examples of using John Snow Labs' NLP for Apache Spark.

text-mining-approach-to-analyze-the-cyber-security-related-articles

In this study, we analyze the "cyber security" related articles (research papers) which have NFS (National Science Foundation) Awards. After downloading the NFS XML files, we parsing them with xml library and convert them tabular format. Then; cleaning, imputing the data. Working on text with NLP techniques (with the help of NLTK and spacy libraries) and finally visualization the result with matplotlib.

visualization-of-twitter-data-with-ms-power-bi

This visualization and document prepared for the 4. Week assignment of ❝Microsoft Azure Data Engineer Trainee❞ at ITPH Academy.

visualization-with-barcharts-lineplots

This is study is prepared for the Assignmen-4 of the "Applied Plotting, Charting & Data Representation in Python Course" by University of Michigan. In the study, we try to find an answer to the question of "How are the numbers of wins medals from Summer Olympics changed over the years in terms of Turkey and Netherlands?".