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Dallas Craigslist Tickets For Sale By Owner – On Friday, eBay announced it had bought its 28.4 percent stake in Craigslist, giving it back to the San Francisco-based online advertising company.

The company also reached an agreement to dismiss all lawsuits, according to the company’s press release.

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Craigslist’s purchase of eBay’s shares ends a strong relationship between the Web’s largest online marketplaces. In 2008, eBay sued Craigslist to reduce its stake in the company in a move that cost the online marketplace its board seat. Craigslist later bought back all of eBay’s stock, but did not appoint an eBay representative to the board.

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EBay bought a stake in Craigslist in 2004 for $32 million, paying $16 million to then-distressed shareholder Phillip Knowlton and $8 million each to Craigslist founders Craig Newmark and Jim Buckmaster. I’ve been wanting Craigslist for a long time. Trying to sell everywhere.

“We really want to buy from Craigslist and we’re willing to buy anything,” he said in Delaware court during eBay’s lawsuit against Craigslist.

Plans for Friday have not been disclosed. According to a report by AIM Group, Craigslist had $269 million in revenue and $335 million in revenue.

. The marketplace company said it will roll out its payments in the third quarter of this year. Using Python and the BeautifulSoup library to analyze the web is one of the many ways to get data from the web. Best of all, An API would be better for this purpose, but Craigslist doesn’t allow me to get the data I need.

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I’ve put all the code on my GitHub if you want to follow along in a Jupyter Notebook.

For any city on Craigslist, you have the opportunity to view ads from individual sellers and buyers. We chose to take the data from private sellers because these ads contain actual information about the vehicle for sale. I chose columns and images because I wanted to take images for advanced topics like image recognition and NLP.

We enter the required data on each traffic posting page as shown on the right side of the image below. Don’t worry if everything in the image below doesn’t make sense. We’ll get there soon.

After browsing the web I was able to come up with a game plan for how I would build my code.

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First, we’ll open the Jupyter directory and import the required libraries. We import.

The next step is to create a list of cities you want to travel to on Craigslist. These city names should be spelled exactly as they appear on Craigslist. If it’s not sfbay in San Francisco, for example, you’ll get a not found error page.

Now we get the links to each page in the city and then we have a list of all the pages for each city. Each page has 120 ads. So to go to next page we need to increase buffer to 120 to get next page. We continue this cycle until page 1800 or so. I chose 1800 because the posts on that page are usually thirty days old. The end result is a list of links to all pages for each city.

Get links to individual city pages; We use a loop to change the city name in the city link.

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What we do is take a city link from a website and create a destination link with the option to change the city name and page number. Something like “https://sfbay.craigslist.org/d/cars-trucks-by-owner/search/cto?s=1&hasPic=1” will convert us to the code shown in line 12.

After using the above code, Each foreign city has a list of links to available pages.

List. Below is an excerpt of what page links look like. For all 15 cities we got 225 link pages, each with 120 traffic posts.

Section, Go to each page and get links to each column of each trend. 225 pages with 120 readings. Let’s end up with a total of 27,000 connections. All 27,000 refer to a specific car post on Craigslist.

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To get traffic links; We loop through the links from each page from the list created above and get 120 posts per page. We store these links in a list called a database.

Get links to each post; We use BeautifulSoup to extract links from web pages. To do this, Passes a link to the app library’s get method, which returns a response code.

If there is a link. We pass the request object to an instance of BeautifulSoup and add an error.

You can find where the links are by right clicking on your chrome browser and selecting browser. The following text will appear with the html structure of the page.

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Tag but because the html object has multiple hrefs; We need to tell you which broth.

We can store these links in a csv or data frame for future reference. Full code to get all traffic links is shown below.

We now see that we have 24706 traffic posts and links, and we can direct BeautifulSoup to pull data from them, but we’ll save a copy first so we can come back to it from time to time. This step is easy; Save as csv file only.

Now that we have all the connections we need, let’s analyze the details of the vehicle. For this we’ll use BeautifulSoup again, but this time we’ll check each ad page for traffic.

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Module and the resulting BeautifulSoup object. The BS object’s search methods are then used to capture traffic attributes and other data from the page. for example, For the price we look for the price.

Now we get all the traffic results from our 27K traffic links and store them in the directory. Made some minor cleanups like creating attribute labels and removing dollar signs and symbols from prices.

Later on, We need to store this data for future analysis. What I’m doing is creating a dictionary with attribute labels as key names. To do this, I am the key I create a dictionary of value pairs, each pointing to a column name, and store the dictionaries in an array.

That’s it, people. For now, at least, we’ve successfully extracted data from Craigslist. We now have 24,000 data and vehicles from 15 cities across the US over a one-month period.

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Please, in the next episode. The Craigslist Cars For Sale Data Project: Part 3 — Data Cleanup; Join me as we do some much-needed data cleanup, such as modifying various data and creating new columns. Also let me know if you have any feedback on the above process. Thank you!

Data scientists should think like architects when looking for a solution when creating a piece of code. ⚪️ Artists love to work on interesting problems that don’t have clear answers ⚪️ linktr.ee/mlearning 🔵 Follow us to join our 28K+ Unique DAILY Readers 🟠

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April home sales in the greater Greenville area were down from the same period last year. However, local and state house prices continue to rise.

More than 1,400 homes changed hands last month, down slightly from March and the same month last year, according to real estate brokers’ market reports.

Greenville home sales in the past five months have increased over a year ago, while the rest of the state has fallen in nine of the past 10 months.

Homes in the area sold for a median price of $298,000 in April, up nearly $50,000 from a year earlier and up $81,100 from before the pandemic. Across South Carolina, home sales rose to a median price of $314,800, an increase of $51,300 over the previous year.

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The National Association of Home Builders expects home sales to decline, with the number of adults planning to buy a home within a year falling at least from the mid-2020s.

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