New Zealand's main stock market index, the NZX 50, rose to 13503 points on December 2, 2025, gaining 0.40% from the previous session. Over the past month, the index has declined 0.39%, though it remains 3.13% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from New Zealand. New Zealand Stock Market (NZX 50) - values, historical data, forecasts and news - updated on December of 2025.

New Zealand Gross Index: NZX 50 data was reported at 8,823.540 03Mar2003=1880.85 in Nov 2018. This records an increase from the previous number of 8,752.310 03Mar2003=1880.85 for Oct 2018. New Zealand Gross Index: NZX 50 data is updated monthly, averaging 3,645.742 03Mar2003=1880.85 from Apr 2003 (Median) to Nov 2018, with 188 observations. The data reached an all-time high of 9,351.060 03Mar2003=1880.85 in Sep 2018 and a record low of 2,013.312 03Mar2003=1880.85 in Apr 2003. New Zealand Gross Index: NZX 50 data remains active status in CEIC and is reported by New Zealand Stock Exchange. The data is categorized under Global Database’s New Zealand – Table NZ.Z001: New Zealand Stock Exchange: Market Indices.

Actual value and historical data chart for New Zealand Stock Market Return Percent Year On Year

Service for each NZTopo50 map sheet holding extents of each sheet. This is the same information that is printed on each NZTopo50 map

Data Dictionary for linz NZTopo50K: https://docs.topo.linz.govt.nz/data-dictionary/tdd-index-obj-A.html

This layer is a service of the NZTopo50 map series. The Topo50 map series provides topographic mapping for the New Zealand mainland, Chatham and New Zealand's offshore islands, at 1:50,000 scale. Georeferenced raster digital images are provided at a resolution of 300 DPI. Georeferencing allows adjacent maps to be accurately and automatically aligned within GIS systems.

Further information on Topo50: https://www.linz.govt.nz/products-services/maps/new-zealand-topographic-maps/topo50-map-chooser

Comprehensive ranking dataset of the top 100 YouTube channels from New Zealand. This dataset features 100 channels with detailed statistics including subscriber counts, total video views, video count, and global rankings. The leading channel has 1,120,000 subscribers and 64,258,833 total views. Each entry includes comprehensive metrics to analyze channel performance, growth trends, and competitive positioning. This dataset is regularly updated to reflect the latest YouTube channel statistics and ranking changes, providing valuable insights for content creators, marketers, and researchers analyzing YouTube ecosystem trends and channel performance benchmarks.

This is a comprehensive data sets of almost all the largest stock market indices of the world. I am confident that this data set would make a significant contribution in financial data analytics. These indices include: 1. S&P 500 (^GSPC) 2. Dow 30 (^DJI) 3. Nasdaq (^IXIC) 4. NYSE COMPOSITE DJ (^NYA) 5. NYSE AMEX COMPOSITE INDEX (^XAX) 6. Cboe UK 100 (^BUK100P) 7. Russell 2000 (^RUT) 8. CBOE Volatility Index (^VIX) 9. DAX PERFORMANCE-INDEX (^GDAXI) 10. CAC 40 (^FCHI) 11. ESTX 50 PR.EUR (^STOXX50E) 12. Euronext 100 Index (^N100) 13. BEL 20 (^BFX) 14. MOEX Russia Index (IMOEX.ME) 15. Nikkei 225 (^N225) 16. HANG SENG INDEX (^HSI) 17. SSE Composite Index (000001.SS) 18. Shenzhen Index (399001.SZ) 19. S&P/ASX 200 (^AXJO) 20. ALL ORDINARIES (^AORD) 21. S&P BSE SENSEX (^BSESN) 22. Jakarta Composite Index (^JKSE) 23. S&P/NZX 50 INDEX GROSS (^NZ50) 24. KOSPI Composite Index (^KS11) 25. TSEC weighted index (^TWII) 26. S&P/TSX Composite index (^GSPTSE) 27. IBOVESPA (^BVSP) 28. IPC MEXICO (^MXX) 29. S&P/CLX IPSA (^IPSA) 30. MERVAL (^MERV) 31. TA-125 (^TA125.TA) 32. EGX 30 Price Return Index (^CASE30) 33. Top 40 USD Net TRI Index (^JN0U.JO)

A structure on top of a hill, usually coloured black and white, used as a physical reference point by surveyors to determine location. The symbol shown on the map includes the elevation and trig identification code for beaconed trig stations. These topographic trig points are derived from New Zealand geodetic marks data which can also be accessed through the LINZ Data Service: NZ Geodetic Marks and NZ Geodetic Vertical Marks.

Data Dictionary for trig_pnt: http://apps.linz.govt.nz/topo-data-dictionary/index.aspx?page=class-trig_pnt

This layer is a component of the Topo50 map series. The Topo50 map series provides topographic mapping for the New Zealand mainland, Chatham and New Zealand's offshore islands, at 1:50,000 scale.

Further information on Topo50: http://www.linz.govt.nz/topography/topo-maps/topo50

New Zealand NZ: Imports: Lead Time: Median Case data was reported at 3.000 Day in 2012. This records an increase from the previous number of 1.590 Day for 2010. New Zealand NZ: Imports: Lead Time: Median Case data is updated yearly, averaging 2.200 Day from Dec 2007 (Median) to 2012, with 3 observations. The data reached an all-time high of 3.000 Day in 2012 and a record low of 1.590 Day in 2010. New Zealand NZ: Imports: Lead Time: Median Case data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Trade Statistics. Lead time to import is the median time (the value for 50 percent of shipments) from port of discharge to arrival at the consignee. Data are from the Logistics Performance Index survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments). The data are exponentiated averages of the logarithm of single value responses and of midpoint values of range responses for the median case.; ; World Bank and Turku School of Economics, Logistic Performance Index Surveys. Data are available online at : http://www.worldbank.org/lpi. Summary results are published in Arvis and others' Connecting to Compete: Trade Logistics in the Global Economy, The Logistics Performance Index and Its Indicators report.; Unweighted average;

New Zealand NZ: Exports: Lead Time: Median Case data was reported at 2.000 Day in 2012. This records an increase from the previous number of 1.260 Day for 2010. New Zealand NZ: Exports: Lead Time: Median Case data is updated yearly, averaging 1.900 Day from Dec 2007 (Median) to 2012, with 3 observations. The data reached an all-time high of 2.000 Day in 2012 and a record low of 1.260 Day in 2010. New Zealand NZ: Exports: Lead Time: Median Case data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s New Zealand – Table NZ.World Bank: Trade Statistics. Lead time to export is the median time (the value for 50 percent of shipments) from shipment point to port of loading. Data are from the Logistics Performance Index survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments). The data are exponentiated averages of the logarithm of single value responses and of midpoint values of range responses for the median case.; ; World Bank and Turku School of Economics, Logistic Performance Index Surveys. Data are available online at : http://www.worldbank.org/lpi. Summary results are published in Arvis and others' Connecting to Compete: Trade Logistics in the Global Economy, The Logistics Performance Index and Its Indicators report.; Unweighted average;

In a survey conducted in 2025 among New Zealanders on their views of tourism, the leading measure participants would like to see implemented to mitigate the environmental impacts of tourism in the country is efforts to educate visitors and locals about why they need to protect and preserve the country's environment, with around 50 percent of respondents indicating this.

A natural, flowing body of water emptying into an ocean, lake or other body of water and usually fed along it's course by converging tributaries.

Data Dictionary for river_poly: https://docs.topo.linz.govt.nz/data-dictionary/tdd-class-river_poly.html

This layer is a component of the Topo50 map series. The Topo50 map series provides topographic mapping for the New Zealand mainland, Chatham and New Zealand's offshore islands, at 1:50,000 scale.

Further information on Topo50: http://www.linz.govt.nz/topography/topo-maps/topo50

The NZD/USD exchange rate fell to 0.5730 on December 2, 2025, down 0.11% from the previous session. Over the past month, the New Zealand Dollar has strengthened 0.39%, but it's down by 2.68% over the last 12 months. New Zealand Dollar - values, historical data, forecasts and news - updated on December of 2025.

This dataset defines the Mean High Water coastline of New Zealand and offshore islands at a scale of 1:50,000, and describes the type of coast along the coastline, for example, steep coast, mangrove, or stony shore.

Purpose The NZ Coastline – Mean High Water dataset is the first step towards improving the national coastline data for New Zealand. LINZ is currently working on a long-term project, “Coastal Mapping” to capture a range of national coastlines derived from LiDAR and bathymetry. This will enable us to generate coastlines, for example, for Mean High Water Springs, Chart Datum and Highest Astronomical Tide. The project is currently focused on capturing LiDAR and bathymetry data, and the timeframe for delivering the new coastlines will be established once the data capture has progressed.

Status This dataset was created and is maintained from LINZ Hydrographic and Topographic sources. Originally created in August 2020, this dataset will be replaced by a more accurate dataset once data becomes available through the Coastal Mapping project.

Data sources and preparation The spatial coastline data (1:50,000 scale) is sourced from the Topo50 series where it is described as a line forming the boundary between the land and sea, defined by mean high water. The source polygon data has been broken up into line segments to enable a coastal classification to be attributed to each segment of coast. Coastal classification data is based on official Electronic Navigational Charts published by the New Zealand Hydrographic Authority. Not all segments have been assigned a coastal category.

APIs and web services This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services "https://linz.maps.arcgis.com/home/item.html?id=45707a4dbee441d293b3fea88fa65309">ArcGIS Online map services

LINZ Data Service (LDS) Item Page - https://data.linz.govt.nz/layer/105085-nz-coastline-mean-high-water/PurposeThe NZ Coastline – Mean High Water dataset is the first step towards improving the national coastline data for New Zealand. LINZ is currently working on a long-term project, “Coastal Mapping” to capture a range of national coastlines derived from LiDAR and bathymetry. This will enable us to generate coastlines, for example, for Mean High Water Springs, Chart Datum and Highest Astronomical Tide. The project is currently focused on capturing LiDAR and bathymetry data, and the timeframe for delivering the new coastlines will be established once the data capture has progressed.StatusThis dataset was created from LINZ Hydrographic and Topographic sources in August 2020 and will not be maintained in this form. This dataset will be replaced by a more accurate dataset in the future once data becomes available through the Coastal Mapping project.Data sources and preparationThe spatial coastline data (1:50,000 scale) is sourced from the Topo50 series where it is described as a line forming the boundary between the land and sea, defined by mean high water. The source polygon data has been broken up into line segments to enable a coastal classification to be attributed to each segment of coast. Coastal classification data is based on official Electronic Navigational Charts published by the New Zealand Hydrographic Authority. Not all segments have been assigned a coastal category.If you have any questions, please contact us at maps@linz.govt.nz

An imaginary line that connects points of equal height value eg the elevation of the land surface above or below a vertical datum, in this case of LINZ topographic mapping, this is Mean Sea Level.

Data Dictionary for contour: https://docs.topo.linz.govt.nz/data-dictionary/tdd-class-contour.html

This layer is a component of the Topo50 map series. The Topo50 map series provides topographic mapping for the New Zealand mainland, Chatham and New Zealand's offshore islands, at 1:50,000 scale.

Further information on Topo50: http://www.linz.govt.nz/topography/topo-maps/topo50

This is an Australian extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).AWS data licence is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.A world speedtest open data was dowloaded (>400Mb, 7M lines of data). An extract of Australia's location (lat, long) revealed 88,000 lines of data (attached as csv).A Jupyter notebook of extract process is attached.See Binder version at Github - https://github.com/areff2000/speedtestAU.+> Install: 173 packages | Downgrade: 1 packages | Total download: 432MBBuild container time: approx - load time 25secs.=> Error: Timesout - BUT UNABLE TO LOAD GLOBAL DATA FILE (6.6M lines).=> Error: Overflows 8GB RAM container provided with global data file (3GB)=> On local JupyterLab M2 MBP; loads in 6 mins.Added Binder from ARDC service: https://binderhub.rc.nectar.org.auDocs: https://ardc.edu.au/resource/fair-for-jupyter-notebooks-a-practical-guide/A link to Twitter thread of outputs provided.A link to Data tutorial provided (GitHub), including Jupyter Notebook to analyse World Speedtest data, selecting one US State.Data Shows: (Q220)- 3.1M speedtests | 762,000 devices |- 88,000 grid locations (600m * 600m), summarised as a point- average speed 33.7Mbps (down), 12.4M (up) | Max speed 724Mbps- data is for 600m * 600m grids, showing average speed up/down, number of tests, and number of users (IP). Added centroid, and now lat/long.See tweet of image of centroids also attached.NB: Discrepancy Q2-21, Speedtest Global shows June AU average speedtest at 80Mbps, whereas Q2 mean is 52Mbps (v17; Q1 45Mbps; v14). Dec 20 Speedtest Global has AU at 59Mbps. Could be possible timing difference. Or spatial anonymising masking shaping highest speeds. Else potentially data inconsistent between national average and geospatial detail. Check in upcoming quarters.NextSteps:Histogram - compare Q220, Q121, Q122. per v1.4.ipynb.Versions:v43. Added revised NZ vs AUS graph for Q325 (NZ; Q2 25) since had NZ available from Github (link below). Calc using PlayNZ.ipynb notebook. See images in Twitter - https://x.com/ValueMgmt/status/1981607615496122814v42: Added AUS Q325 (97.6k lines avg d/l 165.5 Mbps (median d/l 150.8 Mbps) u/l 28.08 Mbps). Imported using v2 Jupyter notebook (MBP 16Gb). Mean tests: 24.5. Mean devices: 6.02. Download, extract and publish: UNK - not measured mins. Download avg is double Q423. Noting, NBN increased D/L speeds from Sept '25; 100 -> 500, 250 -> 750. For 1Gbps, upload speed only increased from 50Mbps to 100Mbps. New 2Gbps services introduced on FTTP and HFC networks.v41: Added AUS Q225 (96k lines avg d/l 130.5 Mbps (median d/l 108.4 Mbps) u/l 22.45 Mbps). Imported using v2 Jupyter notebook (MBP 16Gb). Mean tests: 17.2. Mean devices: 5.11. Download, extract and publish: 20 mins. Download avg is double Q422.v40: Added AUS Q125 (93k lines avg d/l 116.6 Mbps u/l 21.35 Mbps). Imported using v2 Jupyter notebook (MBP 16Gb). Mean tests: 16.9. Mean devices: 5.13. Download, extract and publish: 14 mins.v39: Added AUS Q424 (95k lines avg d/l 110.9 Mbps u/l 21.02 Mbps). Imported using v2 Jupyter notebook (MBP 16Gb). Mean tests: 17.2. Mean devices: 5.24. Download, extract and publish: 14 mins.v38: Added AUS Q324 (92k lines avg d/l 107.0 Mbps u/l 20.79 Mbps). Imported using v2 Jupyter notebook (iMac 32Gb). Mean tests: 17.7. Mean devices: 5.33.Added github speedtest-workflow-importv2vis.ipynb Jupyter added datavis code to colour code national map. (per Binder on Github; link below).v37: Added AUS Q224 (91k lines avg d/l 97.40 Mbps u/l 19.88 Mbps). Imported using speedtest-workflow-importv2 jupyter notebook. Mean tests:18.1. Mean devices: 5.4.v36 Load UK data, Q1-23 and compare to AUS and NZ Q123 data. Add compare image (au-nz-ukQ123.png), calc PlayNZUK.ipynb, data load import-UK.ipynb. UK data bit rough and ready as uses rectangle to mark out UK, but includes some EIRE and FR. Indicative only and to be definitively needs geo-clean to exclude neighbouring countries.v35 Load Melb geo-maps of speed quartiles (0-25, 25-50, 50-75, 75-100, 100-). Avg in 2020; 41Mbps. Avg in 2023; 86Mbps. MelbQ323.png, MelbQ320.png. Calc with Speedtest-incHist.ipynb code. Needed to install conda mapclassify. ax=melb.plot(column=...dict(bins[25,50,75,100]))v34 Added AUS Q124 (93k lines avg d/l 87.00 Mbps u/l 18.86 Mbps). Imported using speedtest-workflow-importv2 jupyter notebook. Mean tests:18.3. Mean devices: 5.5.v33 Added AUS Q423 (92k lines avg d/l 82.62 Mbps). Imported using speedtest-workflow-importv2 jupyter notebook. Mean tests:18.0. Mean devices: 5.6. Added link to Github.v32 Recalc Au vs NZ for upload performance; added image. using PlayNZ Jupyter. NZ approx 40% locations at or above 100Mbps. Aus

Inflation Rate in New Zealand increased to 3 percent in the third quarter of 2025 from 2.70 percent in the second quarter of 2025. This dataset provides - New Zealand Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in New Zealand increased to 5.30 percent in the third quarter of 2025 from 5.20 percent in the second quarter of 2025. This dataset provides - New Zealand Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average House Prices in New Zealand increased to 902020 NZD in October from 900521 NZD in September of 2025. This dataset includes a chart with historical data for New Zealand Average House Prices.