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Businesses relying on Yatra hotels data extraction trust Actowiz Solutions.

Collect high-quality, accurate hotel data from the world's leading Yatra hotels data scraping and marketplaces.

What Types of Data are Typically Extracted When Scraping Yatra Hotel Information?

When scraping Yatra hotel information, typically extracted data includes hotel reviews, ratings, pricing, location details, and amenities. Yatra hotels data scraping provides valuable insights by extracting hotel reviews from Yatra, scraping Yatra for hotel data, and conducting Yatra hotel price scraping for competitive analysis and informed decision-making.

  • Hotel Name
  • Address
  • City
  • State/Province
  • Country
  • ZIP/Postal Code
  • Contact Number
  • Email Address
  • Website URL
  • Star Rating
  • Number of Reviews
  • Average Rating
  • Room Types
  • Room Prices
  • Amenities
  • Check-in Time
  • Check-out Time
  • Nearby Attractions
  • Guest Reviews
  • Review Date
  • Reviewer Name
  • Reviewer Country
  • Review Rating
  • Review Title
  • Review Content
  • Review Responses from Hotel
  • Photos
  • Popularity Ranking
  • Booking Availability
  • Special Offers or Discounts
What-Types-of-Data-are-Typically-Extracted-When-Scraping-Grocery-Supermarket-Information
Inspiration-Awaits-Sample-Travel-Delivery-Data-Showcase-01

Inspiration Awaits: Sample Yatra Data Showcase

Take a look at our curated sample Yatra data and get inspired. See the impact of detailed hotel data insights on innovation and strategy development.

See Data Samples

No matter the shape or size, we capture all data. Our extensive range ensures you get the complete and detailed data you need for any application.

  • Hotel Details Extraction

    Extract comprehensive hotel details such as name, address, contact information, and star rating from Yatra for accurate and up-to-date information.

  • Room Information Collection

    Gather detailed room information, including room types, prices, and availability, to provide insights into accommodation options and pricing structures.

  • Review Data Extraction

    Capture extensive guest review data, including review titles, content, ratings, and dates, for a thorough understanding of customer feedback and satisfaction.

  • Amenity Listings

    Collect information on hotel amenities such as Wi-Fi, parking, pool, gym, and breakfast options to understand the facilities offered by each hotel.

  • Location Insights

    Extract location data, including proximity to landmarks and attractions, helping to assess the hotel’s convenience and attractiveness to potential guests.

  • Image Scraping

    Retrieve high-quality images of the hotel, rooms, and amenities to provide a visual understanding of the property and its offerings.

  • Ranking Information

    Gather hotel popularity rankings and ratings from Yatra, offering insights into the hotel’s standing and reputation among travelers.

  • Contact Information

    Extract essential contact details like phone numbers and email addresses to facilitate direct communication with the hotel management.

  • Special Offers Collection

    Capture data on special offers, discounts, and packages provided by hotels, helping to keep track of promotional deals and seasonal offers.

No-matter-the-shape-or-size-we-capture-all-data

Explore the Best Techniques to Collect Hotel Data

Premium-Industry-Datasets-on-Demand
Web Scraping Solutions

Our web scraping services encompass your target hotel websites, delivering data in a standardized schema. This approach streamlines your workflow and saves you valuable time and resources.

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Experience the leading web scraping API, meticulously designed to sidestep bans with ease, maximizing cost-effectiveness and streamlining your project timeline.

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Our web scrapers offers advanced tools for comprehensive data extraction from diverse sources, ensuring optimized web scraping capabilities. Trust us to get innovative solutions tailored to your specific requirements.

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Enterprise-Ready Solutions

Enterprise-Ready Solutions for Robust Data Extraction and Integration. Our advanced tools and expertise ensure seamless integration and scalable performance, meeting the rigorous demands of large-scale data extraction projects.

Enterprise Solution

How to get hotel delivery details from Yatra site?

Market Analysis

Yatra hotels data scraping helps analyze market trends by extracting hotel reviews from Yatra, aiding strategic decision-making and competitive analysis.

Customer Sentiment

Extract hotel reviews from Yatra to understand customer sentiment, enhancing service quality and improving guest experiences through actionable insights.

Pricing Strategy

Utilize Yatra hotel price scraping to compare room rates, helping optimize pricing strategies for better revenue management and competitive positioning.

Quality Assessment

Scraping Yatra hotel ratings allows for evaluating hotel performance, identifying strengths and areas for improvement in guest services.

Visual Content

Extract hotel images from Yatra to enhance marketing materials, providing potential guests with accurate visuals of the hotel and its amenities.

Comprehensive Data

Web scraping Yatra for hotel data gathers detailed information on hotel facilities, location, and reviews, supporting comprehensive property analysis.

Travel Insights

Scraping Yatra for travel analytics provides valuable insights into traveler preferences and behaviors, aiding in targeted marketing and personalized guest experiences.

Automated Collection

Web crawler for Yatra hotels automates data extraction, ensuring efficient and consistent collection of essential hotel information for various applications.

Data Services

Yatra hotel data extraction services offer tailored solutions for businesses needing accurate and up-to-date hotel data to support operations and strategic planning.

Frequently Asked Questions

You can receive your data through various methods such as SFTP, FTP, email, Dropbox, Google Cloud storage, AWS S3, or Google Drive. We offer delivery in JSON, CSV, XML, or JSONLines formats, tailored to your project needs. Custom delivery options are also available upon request to meet specific requirements.
While we possess the technical capability to extract data from any website, each project must adhere to legal considerations. This includes scraping behind logins and compliance with privacy policies, terms and conditions, and copyright laws. Our solution architects and legal team assess each project to ensure adherence to web scraping best practices and legal requirements.
After submitting your project request, a member of our solution architecture team will promptly initiate a project discovery call. They will delve into your hotel data scraping requirements, including which sites to crawl, specific data extraction needs, the scope of scraping, data transformation requirements, and necessary integrations. Once gathered, our architects will propose tailored hotel data scraping solutions within a few days for your approval.
Our expertise lies in data extraction solutions designed for mission-critical business needs, prioritizing the delivery of high-quality, accurate data to our clients. Implementing a rigorous four-layer Data Quality Assurance process ensures continuous monitoring of crawl health and data accuracy through manual, semi-automated, and automated testing. Count on us for reliable hotel data scraping services, including online store data scraping and competitor price monitoring.
We provide complimentary support to all our customers for coverage issues, missed deliveries, and minor site changes. Larger website data extraction changes that require a complete spider overhaul may invite additional costs.
Yes, if sample data is available for the source you wish to scrape, we can provide it. For new sources not previously crawled, sample data will be shared after the development kick-off, which occurs post-purchase. Additionally, for product or news & article data, you can trial our Automatic Extraction product with a user-friendly interface for free.
Actowiz offers comprehensive Data Extraction services, providing hassle-free web content extraction for clean, structured data quickly and accurately. Alternatively, Actowiz also provides DIY web data extraction tools for those preferring a hands-on approach.
Data extraction refers to the process of retrieving specific information or datasets from various sources such as databases, websites, or documents. It involves systematically gathering relevant data for analysis, reporting, or storage purposes. This method is crucial in industries like finance, healthcare, and hotel, where accessing and analyzing large volumes of data is essential for decision-making. Data extraction typically utilizes tools and techniques such as web scraping, API calls, or database queries to fetch structured data. The extracted data is then transformed and loaded into a format suitable for analysis, enabling businesses to derive insights, improve efficiency, and support strategic initiatives.
Data extraction is crucial as it enables organizations to access, collect, and utilize valuable information from diverse sources efficiently. By extracting data from databases, websites, or other repositories, businesses can derive actionable insights, improve decision-making processes, and enhance operational efficiency. This process is particularly vital in industries like finance, healthcare, and retail, where analyzing large datasets helps in trend analysis, customer behavior understanding, and market forecasting. Data extraction also supports compliance with regulatory requirements by ensuring accurate reporting and data governance. Overall, it empowers organizations to leverage data-driven strategies, innovate products and services, and maintain a competitive edge in the market.
Certainly! An example of data extraction could involve extracting customer information from an hotel website. Using web scraping techniques, specific data such as customer names, email addresses, purchase histories, and preferences can be gathered from multiple pages of the website. This extracted data can then be structured into a format like CSV or JSON for further analysis or integration into a customer relationship management (CRM) system. By automating this process, businesses can streamline customer data management, personalize marketing efforts, and improve customer service strategies based on insights derived from the extracted data.
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GeoIp2\Model\City Object
(
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                            [en] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [zh-CN] => 北美洲
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                            [ru] => США
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                                    [fr] => Ohio
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                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
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        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
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                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [0] => confidence
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                    [4] => names
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        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                        (
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        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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            [validAttributes:protected] => Array
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                    [1] => autonomousSystemOrganization
                    [2] => connectionType
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                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
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        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [names] => Array
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                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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        )

    [location:protected] => GeoIp2\Record\Location Object
        (
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            [validAttributes:protected] => Array
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                    [1] => accuracyRadius
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                    [7] => postalConfidence
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    [postal:protected] => GeoIp2\Record\Postal Object
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            [validAttributes:protected] => Array
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    [subdivisions:protected] => Array
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                                    [es] => Ohio
                                    [fr] => Ohio
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                                )

                        )

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)
 country : United States
 city : Columbus
US
Array
(
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    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
Array
(
    [city] => Columbus
    [country] => United States
    [countryCode] => +1
    [currencyCode] => USD
)
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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

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                )

            [postal] => Array
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            [registered_country] => Array
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                    [iso_code] => US
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
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                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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