Imports from United Kingdom in France increased to 2310 EUR Million in January from 2218 EUR Million in December of 2023. This dataset includes a chart with historical data for France Imports from Uk.

This dataset is about books. It has 22 rows and is filtered where the book subjects is British-France. It features 9 columns including author, publication date, language, and book publisher.

Our Europe B2B Data is a powerhouse of business intelligence, offering a comprehensive repository of over 52 million contacts, comprising decision-makers, owners, and founders. Delving into the intricacies of our dataset, here's what makes it a cut above the rest:

1. Unrivaled Accuracy: With verified email addresses, direct dials, and 16+ attributes, our data boasts an unparalleled accuracy rate of 100%. This ensures that your outreach efforts are targeted and effective, minimizing bounce rates and maximizing ROI.

2. Extensive Coverage: Spanning across various industries and countries, our dataset provides extensive coverage, enabling you to access key contacts from diverse sectors. From finance and healthcare to technology and manufacturing, we've got you covered.

3. Scale and Quality: Backed by high-scale and quality indicators, our data undergoes rigorous verification and validation processes to maintain its integrity and reliability. This ensures that you're working with the most up-to-date and actionable information available.

4. Sourcing Methodology: Our data is sourced from a multitude of reputable sources, including public records, industry-specific directories, and strategic partnerships with leading data providers. This multi-sourced approach ensures comprehensive coverage and accuracy.

5. Primary Use-Cases: Whether you're looking to expand your customer base, conduct market research, or enhance your B2B marketing campaigns, our dataset caters to a myriad of use cases. With detailed insights into key decision-makers, you can tailor your strategies for maximum impact.

6. Verticals and Industries: From startups to enterprise-level organizations, our data serves a wide array of verticals and industries. Some of the sectors covered include finance, healthcare, IT, manufacturing, retail, and more.

7. List of Countries in Europe: Our dataset covers the entire European continent, including but not limited to:

   • United Kingdom
   • Germany
   • France
   • Italy
   • Spain
   • Netherlands
   • Switzerland
   • Sweden
   • Belgium
   • Austria
   • Denmark
   • Finland
   • Norway
   • Ireland
   • Portugal
   • Greece
   • Poland
   • Czech Republic
   • Hungary
   • And many more.

In the broader context of our data offering, Europe B2B Data seamlessly integrates with our suite of global B2B data solutions. Whether you're targeting specific regions or expanding your reach globally, our datasets provide the foundation for success in today's competitive business landscape.

Industries We Cover: - Our dataset spans across a wide range of industries, including: - Technology - Finance - Healthcare - Manufacturing - Retail - Hospitality - Education - Real Estate - Transportation - Energy - Media & Entertainment - Agriculture - and many others.

Harness the power of our Europe B2B Data to unlock new opportunities, drive growth, and stay ahead of the curve in your industry. With its unmatched accuracy, extensive coverage, and versatile applications, our data is the key to unlocking your business's full potential.

Exports to United Kingdom in France increased to 3113 EUR Million in January from 2811 EUR Million in December of 2023. This dataset includes a chart with historical data for France Exports to Uk.

Our Point of Interest (POI) data supports various location intelligence projects and facilitates the development of precise mapping and navigation tools, location analysis, address validation, and much more. Gain access to highly accurate, clean, and globally scaled POI data featuring over 164 million verified locations across 220 countries. We have been providing this data to companies worldwide for 30 years.

• Develop mapping and navigation tools and software.
• Identify new areas and locations suitable for business development.
• Analyze the presence of competitors and nearby populations.
• Optimize routes to enhance delivery efficiency.
• Evaluate property values based on nearby infrastructure.
• Support disaster management by identifying high-risk areas.
• Promote your products and services using geotargeting strategies.

Our use cases demonstrate how our data has been beneficial and helped our customers in several key areas: 1. Gaining a Competitive Edge: Utilize point of interest (POI) data to analyze competitors, identify high-opportunity areas, and attract more customers. 2. Enhancing Customer Journeys: Leverage location intelligence to provide personalized, real-time recommendations that boost customer engagement. 3. Optimizing Store Expansion: Select the most profitable locations by analyzing foot traffic, demographics, and competitor insights. 4. Streamlining Deliveries: Improve fulfillment accuracy through address validation, reducing failed shipments and increasing customer satisfaction. 5. Driving Smarter Campaigns: Use geospatial insights to effectively target the right audiences, enhance outreach, and maximize campaign impact.

EEZ boundary between the UK and France

This dataset is about books. It has 1 row and is filtered where the book is Rivals in arms : the rise of UK-France defence relations in the twenty-first century. It features 7 columns including author, publication date, language, and book publisher.

Unlock the power of 164M+ verified locations across 220+ countries with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

The database includes a list of 1577 weed plant taxa found in cultivated fields of France and UK, along with basic ecological and biogeographical information.
The database is a CSV file in which the columns are separated with comma, and the decimal sign is ".".
It can be imported in R with the command "tax.discoweed <- read.csv("tax.discoweed_18Dec2017_zenodo.csv", header=T, sep=",", dec=".", stringsAsFactors = F)"

Taxonomic information is based on TaxRef v10 (Gargominy et al. 2016),
- 'taxref10.CD_REF' = code of the accepted name of the taxon in TaxRef,
- 'binome.discoweed' = corresponding latine name,
- 'family' = family name (following APG III),
- 'taxo' = taxonomic rank of the taxon, either 'binome' (species level) or 'infra' (infraspecific level),
- 'binome.discoweed.noinfra' = latine name of the superior taxon at species level (different from 'binome.discoweed' for infrataxa),
- 'taxref10.CD_REF.noinfra' = code of the accepted name of the superior taxon at species level.

The presence of each taxon in one or several of the following data sources is reported:
- Species list from a reference flora (observations in cultivated fields over the long term, without sampling protocol),
* 'jauzein' = national and comprehensive flora in France (Jauzein 1995),
- Species lists from plot-based inventories in cultivated fields,
* 'za' = regional survey in 'Zone Atelier Plaine & Val de Sèvre' in SW France (Gaba et al. 2010),
* 'biovigilance' = national survey of cultivated fields in France (Biovigilance, Fried et al. 2008),
* 'fse' = Farm Scale Evaluations in England and Scotland, UK (Perry, Rothery, Clark et al., 2003),
* 'farmbio' = Farm4Bio survey, farms in south east and south west of England, UK (Holland et al., 2013)
- Reference list of segetal species (species specialist of arable fields),
* 'cambacedes' = reference list in France (Cambacedes et al. 2002)

Life form information is extracted from Julve (2014) and provided in the column 'lifeform'.
The classification follows a simplified Raunkiaer classification (therophyte, hemicryptophyte, geophyte, phanerophyte-chamaephyte and liana). Regularly biannual plants are included in hemicryptophytes, while plants that can be both annual and biannual are assigned to therophytes.

Biogeographic zones are also extracted from Julve (2014) and provided in the column 'biogeo'.
The main categories are 'atlantic', 'circumboreal', 'cosmopolitan, 'Eurasian', 'European', 'holarctic', 'introduced', 'Mediterranean', 'orophyte' and 'subtropical'.
In some cases, a precision is included within brackets after the category name. For instance, 'introduced(North America)' indicates that the taxon is introduced from North America.
In addition, some taxa are local endemics ('Aquitanian', 'Catalan', 'Corsican', 'corso-sard', 'ligure', 'Provencal').
A single taxon is classified 'arctic-alpine'.

Red list status of weed taxa is derived for France and UK:
- 'red.FR' is the status following the assessment of the French National Museum of Natural History (2012),
- 'red.UK' is based on the Red List of vascular plants of Cheffings and Farrell (2005), last updated in 2006.
The categories are coded following the IUCN nomenclature.

A habitat index is provided in column 'module', derived from a network-based analysis of plant communities in open herbaceous vegetation in France (Divgrass database, Violle et al. 2015, Carboni et al. 2016).
The main habitat categories of weeds are coded following the Divgrass classification,
- 1 = Dry calcareous grasslands
- 3 = Mesic grasslands
- 5 = Ruderal and trampled grasslands
- 9 = Mesophilous and nitrophilous fringes (hedgerows, forest edges...)
Taxa belonging to other habitats in Divgrass are coded 99, while the taxa absent from Divgrass have a 'NA' value.

Two indexes of ecological specialization are provided based on the frequency of weed taxa in different habitats of the Divgrass database.
The indexes are network-based metrics proposed by Guimera and Amaral (2005),
- c = coefficient of participation, i.e., the propensity of taxa to be present in diverse habitats, from 0 (specialist, present in a single habitat) to 1 (generalist equally represented in all habitats),
- z = within-module degree, i.e., a standardized measure of the frequency of a taxon in its habitat; it is negatve when the taxon is less frequent than average in this habitat, and positive otherwise; the index scales as a number of standard deviations from the mean.

This dataset is about books. It has 1 row and is filtered where the book is Disciplining statistics : demography and vital statistics in France and England, 1830/1885. It features 7 columns including author, publication date, language, and book publisher.

Through two decades of campaigns delivery and optimization, Expandi has created the most comprehensive GDPR-compliant European database covering SMB, Midmarket, and Enterprise companies. Our data base is enriched with up-to-date technographic, financial and intent data. All our data is updated regularly and includes only active companies, allowing you to reach the most relevant and appropriate customers for your business.

Our available data: • Updated company Firmographic, Financial data (revenues, financial strength, profit/loss), Decision Making Unit structure, and Key decision maker contacts (name, job title, LinkedIn profile). • Multi-language buyer intent data coming from omni-channel interactions and scored by brand and solutions. • Technographic and brand preference data. • Company IP addresses and Device ID mapping and tracking to help you identify unknown online traffic and boost the results of your awareness and branding campaigns.

Target selection criteria: • Region / State-Province • Range employees (starting from 50+) • Range Revenues • Industry / Sub-industry • Financial strength • Decision Making Unit • Technographic data • Intent data solution / Intent data stage

Data delivery: One-off purchase.

Let’s start today to boost your demand generation campaigns and raise awareness of your brand and solutions!

This dataset is about books. It has 1 row and is filtered where the book is The relations of history and geography : studies in England, France and the United States. It features 7 columns including author, publication date, language, and book publisher.

505 Economics is on a mission to make academic economics accessible. We've developed the first monthly sub-national GDP data for EU and UK regions from January 2015 onwards.

Our GDP dataset uses luminosity as a proxy for GDP. The brighter a place, the more economic activity that place tends to have.

We produce the data using high-resolution night time satellite imagery and Artificial Intelligence.

This builds on our academic research at the London School of Economics, and we're producing the dataset in collaboration with the European Space Agency BIC UK.

We have published peer-reviewed academic articles on the usage of luminosity as an accurate proxy for GDP.

Key features:

• Granular: Data is provided at the following geographical units:
  • NUTS3 (e.g. London Boroughs),
  • NUTS2 (e.g. London),
  • NUTS1 (e.g. England), and
  • NUTS0 (e.g. United Kingdom) levels.
• Frequent: Data is provided every month from January 2015. This is more frequent than the annualised official datasets.
• Timely: Data is provided with a one month lag (i.e. the data for January 2021 was published at the end of February 2021). This is substantially quicker than the 18 month lag of official datasets.
• Accurate: Our dataset uses Deep Learning to maximise accuracy (RMSE 1.2%).

The dataset can be used by:

• Governments and policy makers - to monitor the performance of local economies, to measure the localised impact of policies, and to get a real-time indication of economic activity.
• Financial services - to get an indication of national-level GDP before official GDP statistics are released
• Engineering companies - to monitor and evaluate the localised impact of infrastructure projects
• Consultancies - to forecast the localised impact of specific projects, to retrospectively monitor and evaluate the localised impact of existing projects
• Economics firms - to create macro forecasts at the national and sub-national level, to assess the impact of policy interventions.
• Academia / Think Tanks - to conduct novel research at the local level. E.g. our dataset can be used to measure the impact of localised COVID-19 lockdowns.

We have created this dataset for all UK sub-national regions, 28 EU Countries and Switzerland.

This dataset is about books. It has 1 row and is filtered where the book publisher is the France & Colonies Philatelic Society of Great Britain. It features 7 columns including author, publication date, language, and book publisher.

Global Spend Analysis with Consumer Edge Credit & Debit Card Transaction Data

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. CE Vision EUR is an aggregated transaction feed that includes consumer transaction data on 6.7M+ Europe-domiciled payment accounts, including 5.3M+ active monthly users. Capturing online, offline, and 3rd-party consumer spending on public and private companies, data covers 4.4K+ brands and 620 symbols including 490 public tickers. Track detailed consumer behavior patterns, including retention, purchase frequency, and cross shop in addition to total spend, transactions, and dollars per transaction.

Consumer Edge’s consumer transaction datasets offer insights into industries across consumer and discretionary spend such as: • Apparel, Accessories, & Footwear • Automotive • Beauty • Commercial – Hardlines • Convenience / Drug / Diet • Department Stores • Discount / Club • Education • Electronics / Software • Financial Services • Full-Service Restaurants • Grocery • Ground Transportation • Health Products & Services • Home & Garden • Insurance • Leisure & Recreation • Limited-Service Restaurants • Luxury • Miscellaneous Services • Online Retail – Broadlines • Other Specialty Retail • Pet Products & Services • Sporting Goods, Hobby, Toy & Game • Telecom & Media • Travel

This data sample illustrates how Consumer Edge data can be used to understand a company’s growth by country for a specific time period (Ex: What was McDonald’s year-over-year growth by country from 2019-2020?)

Inquire about a CE subscription to perform more complex, near real-time global spend analysis functions on public tickers and private brands like: • Analyze year-over-year spend growth for a company for a subindustry by country • Analyze spend growth for a company vs. its competitors by country through most recent time

Consumer Edge offers a variety of datasets covering the US and Europe (UK, Austria, France, Germany, Italy, Spain), with subscription options serving a wide range of business needs.

Use Case: Global Spend Analysis

Problem A global retailer wants to understand company performance by geography to identify growth and expansion opportunities.

Solution Consumer Edge transaction data can be used to analyze shopper behavior across geographies and track: • Growth trends by country vs. competitors • Brand performance vs. subindustry by country • Opportunities for product and location expansion

Impact Marketing and Consumer Insights were able to: • Develop weekly reporting KPI's on key growth drivers by geography for company-wide reporting • Refine strategy in underperforming geographies, both online and offline • Identify areas for investment and expansion by country • Understand how different cohorts are performing compared to key competitors

Corporate researchers and consumer insights teams use CE Vision for:

Corporate Strategy Use Cases • Ecommerce vs. brick & mortar trends • Real estate opportunities • Economic spending shifts

Marketing & Consumer Insights • Total addressable market view • Competitive threats & opportunities • Cross-shopping trends for new partnerships • Demo and geo growth drivers • Customer loyalty & retention

Investor Relations • Shareholder perspective on brand vs. competition • Real-time market intelligence • M&A opportunities

Most popular use cases for private equity and venture capital firms include: • Deal Sourcing • Live Diligences • Portfolio Monitoring

Public and private investors can leverage insights from CE’s synthetic data to assess investment opportunities, while consumer insights, marketing, and retailers can gain visibility into transaction data’s potential for competitive analysis, understanding shopper behavior, and capturing market intelligence.

Most popular use cases among public and private investors include: • Track Key KPIs to Company-Reported Figures • Understanding TAM for Focus Industries • Competitive Analysis • Evaluating Public, Private, and Soon-to-be-Public Companies • Ability to Explore Geographic & Regional Differences • Cross-Shop & Loyalty • Drill Down to SKU Level & Full Purchase Details • Customer lifetime value • Earnings predictions • Uncovering macroeconomic trends • Analyzing market share • Performance benchmarking • Understanding share of wallet • Seeing subscription trends

Fields Include: • Day • Merchant • Subindustry • Industry • Spend • Transactions • Spend per Transaction (derivable) • Cardholder State • Cardholder CBSA • Cardholder CSA • Age • Income • Wealth • Ethnicity • Political Affiliation • Children in Household • Adults in Household • Homeowner vs. Renter • Business Owner • Retention by First-Shopped Period • Churn • Cross-Shop • Average Ticket Buckets

This dataset is about book subjects. It has 5 rows and is filtered where the books is Against the friars : antifraternalism in medieval France and England. It features 2 columns including publication dates.

This dataset is about books. It has 1 row and is filtered where the book is Planning and public transport in Great Britain, France and West Germany. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about book subjects. It has 12 rows and is filtered where the books is Scotland, England and France after the loss of Normandy, 1204-1296 : "Auld Amitie". It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset is about books. It has 1 row and is filtered where the book is Growing skills in Europe : the changing skill profiles of France, Germany, the Netherlands, Portugal, Sweden and the UK. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about book subjects. It has 9 rows and is filtered where the books is The birth of nobility : constructing aristocracy in England and France : 900-1300. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.