Matplotlib is a tremendous visualization library in Python for 2D plots of arrays. Matplotlib may be a multi-platform data visualization library built on NumPy arrays and designed to figure with the broader SciPy stack. It had been introduced by John Hunter within the year 2002.

A bar plot or bar graph may be a graph that represents the category of knowledge with rectangular bars with lengths and heights that’s proportional to the values which they represent. The bar plots are often plotted horizontally or vertically.

A bar chart is a great way to compare categorical data across one or two dimensions. More often than not, it’s more interesting to compare values across two dimensions and for that, a grouped bar chart is needed.

Use the Chart Viewer template to display bar charts, line charts, pie charts, histograms, and scatterplots to complement a map. Include multiple charts to view with a map or side by side with other charts for comparison. Up to three charts can be viewed side by side or stacked, but you can access and view all the charts that are authored in the map. Examples: Present a bar chart representing average property value by county for a given area. Compare charts based on multiple population statistics in your dataset. Display an interactive scatterplot based on two values in your dataset along with an essential set of map exploration tools. Data requirements The Chart Viewer template requires a map with at least one chart configured. Key app capabilities Multiple layout options - Choose Stack to display charts stacked with the map, or choose Side by side to display charts side by side with the map. Manage chart - Reorder, rename, or turn charts on and off in the app. Multiselect chart - Compare two charts in the panel at the same time. Bookmarks - Allow users to zoom and pan to a collection of preset extents that are saved in the map. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows the areas of principal soil groups which are divided into 48 subgroups. Two graphs are included. One is a bar chart showing the principal soil groups and their distribution by provinces and territories. The other is a pie chart displaying the percentage areas of principal soil groups.

This activity (on page 2 of the PDF) is a full inquiry-based challenge related to motion and design optimization. Groups of learners will use construction paper to build a model bobsled run for a marble to follow down a ramp. They are then challenged to get the marble down the ramp in a time of 12 seconds, continuing to modify and re-test their run until they reach this goal. Learners can track their progress by creating a bar chart that shows the speed of each design version. This is a great activity for developing team-building skills. Relates to linked video, DragonflyTV GPS: Luge.

The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal accumulated amounts for various stations around the world. These charts are created for different scales of time (30, 90, 365 days). Each station has a graphic that contains two charts. The first chart in the graphic is a time series in the format of a line graph, representing accumulated precipitation for each day in the time series compared to the accumulated normal amount of precipitation. The second chart is a bar graph displaying actual daily precipitation. The total accumulation and surplus or deficit amounts are displayed as text on the charts representing the entire time scale, in both inches and millimeters. The graphics are updated daily and the graphics reflect the updated observations and accumulated precipitation amounts including the latest daily data available. The available graphics are rotated, meaning that only the most recently created graphics are available. Previously made graphics are not archived.

Tabulating and Visualizing Supermarket Data

In this portfolio, I present an analysis of supermarket data, focusing on total sales, product categories, highest-spending customers, states with the highest and lowest sales, top-selling regions, and the most profitable city. This analysis provides valuable insights into supermarket performance and customer behavior.

Total Sales:

This chart illustrates the total sales over a specific time period. It serves as a key indicator of the supermarket's financial performance, showing revenue trends.

Product Categories:

A pie chart displays the distribution of sales across various product categories. It helps identify which product categories are the most popular and which may require additional marketing efforts.

Highest-Spending Customer:

The bar chart reveals the highest-spending customer, allowing the supermarket to recognize and reward loyal customers, while also gaining insights into their preferences.

States with the Highest Sales:

A map or bar chart showcases the states with the highest sales. This data can inform inventory management and marketing strategies.

Top-Selling Regions:

A bar chart displays the regions that generate the most sales, enabling the supermarket to concentrate resources where they are most effective.

Most Profitable City:

The pie chart reveals the city with the highest sales, providing insights into localized market dynamics.

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Power BI:

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This code runs a sentiment analysis for all of President Lyndon Johnson's speeches that mention the terms "Black," "Civil Rights," "Equality," "Negro" and "Voting Rights." This code also graphs the sentiment analysis in a bar chart. The first six bar charts show the sentiment analysis of the speeches based on date and which word was used, while the final bar chart shows all speeches graphed with their corresponding sentiment analysis.

The global temperature time series provides time series charts using station based observations of daily temperature. These charts provide information about the observations compared to the derived daily normal temperature for various time scales (30, 90, 365 days). Each station has a graphic that contains three charts. The first chart in the graphic is a time series in the format of a line graph, representing the daily average temperatures compared to the expected daily normal temperatures. The second chart is a bar graph displaying daily departures from normal, including a line depicting the mean departure for the period. The third chart is a time series of the observed daily maximum and minimum temperatures. The graphics are updated daily and the graphics reflect the updated observations including the latest daily data available. The available graphics are rotated, meaning that only the most recently created graphics are available. Previously made graphics are not archived.

This map shows population change from 2000 to 2010 by county, tract, and block group. Magenta symbols represent losses in population while blue symbols represent gains. At the national level, the map highlights growth patterns in the west coast, Texas, and the east coast in blue, and areas that have lost population, such as Detroit, New Orleans, and much of the Midwest, in magenta. Areas of larger growth and decline are represented with larger symbols. As you zoom into the map, you activate the gauge symbols. These show the degree of population increase or decrease. The white arrow points to the level of change (blue = increase, magenta = decrease). Click on any of the symbols to view a popup showing the count of population growth or decline, the percent change, and a bar chart comparing 2000 to 2010 population.Story map and layers are found in the Living Atlas.

Highlights from Last WeekData regarding the last week of visitors including a breakdown of adult and child visitor ratio, a visitor counter, and a bar chart displaying the most popular days visited.Adult/child ratios are based on best estimates of the age of visitors.

This data set comprises a series of measurements of GPU power consumption when raycasting spherical glyphs, raycasting scalar fields and when showing web-based data visualisation on Observable HQ. The data sets for sphere rendering were: pos_rad_intensity : 500000 : 0 : 10 10 10 : 0.01 0.1 500,000 spheres placed randomly, but usinga fixed seed, in a box of 10 × 10 × 10 units with a radius between 0.01 and 0.1 pos_rad_intensity : 5000000 : 0 : 10 10 10 : 0.01 0.1 5,000,000 spheres placed randomly, but usinga fixed seed, in a box of 10 × 10 × 10 units with a radius between 0.01 and 0.1 The scalar fields used for the volume rendering were: veiled-chameleon.u8.dat A 1024 × 1024 × 1080 8-bit scalar field of a chameleon foot.dat A 256 × 256 × 256 8-bit scalar field of a human foot The websites visited for the information visualisation application case are: https://observablehq.com/@d3/bar-chart Bar chart https://observablehq.com/@d3/brushable-parallel-coordinates Brushable Parallel Coordinates https://observablehq.com/@d3/density-contours/3 Density Contours https://observablehq.com/@d3/chord-dependency-diagram Chord Dependency Diagram https://observablehq.com/@d3/world-choropleth Choropleth, World https://observablehq.com/@robsutcliffe/dirty-planet/2</a Dirty Planet (WebGL) https://observablehq.com/@mbostock/hertzsprung-russell-diagram Hertzsprung-Russell Diagram https://observablehq.com/@d3/bollinger-bands Line Chart, Bollinger Bands https://observablehq.com/@pamacha/platonic-gobstopper Platonic Gobstopper (WebGL) https://observablehq.com/@observablehq/plot-horizon Plot: Horizon Chart https://observablehq.com/@d3/sankey Sankey Diagram https://observablehq.com/@d3/json-treemap Treemap, JSON https://observablehq.com/@observablehq/vispubdata Visualization Publication Dataset (Multiple visualisations on the same page) https://observablehq.com/@mbostock/yarn-lock-visualizer Yarn.lock Visualizer (Node-link diagram) The power sensors employed include the software sensors by AMD and NVIDIA exposed via ADL and NVML, respectively; Tinkerforge Voltage/Current 2.0 bricklets (for measuring most of the internal power rails of the computer individually) and a power analyser attached between the system and the wall socket. They are designated as follows: ADL/ASIC/{0-6} Power readings obtained from the GPU via the AMD Display Library. HMC Power measurements between system and wall socket obtained from a Rohde & Schwarz HMC8015 NVML Power readings obtained from the gPU via the NVIDIA Management Library TF_ATX_12 Power draw of the ATX 12V rail obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_ATX_3_3 Power draw of the ATX 3.3V rail obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_ATX_5 Power draw of the ATX 5V rail obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_CPU_P4 Power draw of the P4 power connector to the CPU obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_CPU_P8 Power draw of the P8 power connector to the CPU obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_CPU TF_CPU_P4 + TF_CPU_P8 TF_GPU TF_GPU_PCI_12 + TF_GPU_PCI_3_3 + TF_PCIE_1 + TF_PCIE_2 TF_GPU_PCI_12 Power draw of the GPU via the 12V rail of the PEG slot obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_GPU_PCI_3_3 Power draw of the GPU via the 3.3V rail of the PEG slot obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_PCIE_1 Power draw of the GPU via the first PCIe cable obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_PCIE_2 Power draw of the GPU via the second PCIe cable obtained via a Tinkerforge Voltage/Current 2.0 Bricklet TF_SUM The sum of all Tinkerforge Voltage/Current 2.0 Bricklets TF_ATX TF_ATX_12 + TF_ATX_5 + TF_ATX_3_3 - TF_GPU_PCI_12 - TF_GPU_PCI_3_3

Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows six condensed maps of the distribution of plants producing the following: leather footwear, womens and childrens factory made clothing, synthetic textiles and silks, mens factory made clothing, cotton textiles, and rubber products. All data for these maps is for 1954 with the exception of the rubber products map which is for 1955. Each map is accompanied by a bar graph and pie chart. The bar graphs show the value of production by major categories of products. The pie charts show the percentage distribution of persons employed in each manufacturing industry by province.

This Python script visualizes data related to the brand value of the Indian Premier League (IPL), its constituent teams, and a comparison with other major football leagues. It uses matplotlib for creating the plots and numpy for numerical operations. The script generates four key visualizations:

IPL Brand Value Over Time: A line plot illustrating the growth of the IPL's brand value in billion dollars from 2009 to 2024. This chart shows the increasing financial strength and popularity of the league over the years.

Top 10 IPL Team Brand Values (2024): A bar chart displaying the brand values (in million dollars) of the top 10 IPL teams in 2024. This visualization allows for a comparison of the brand strength of different teams within the league. The numerical value of each bar is displayed on top of the bar.

Growth Rate of IPL Team Brand Values (2024): Another bar chart presenting the growth rates (in percentage) of the top 10 IPL teams' brand values in 2024. This plot highlights the teams with the highest growth potential and increasing popularity. The growth rate in percentage is displayed on top of the bar.

Comparison of IPL and Football League Brand Values: A bar chart comparing the brand values (in billion dollars) of the IPL (top 5 teams), Bundesliga, and English Premier League (EPL). This visualization contextualizes the IPL's financial strength in comparison to other prominent sports leagues worldwide.

Figure 8.4 displays a bar chart on age-standardized emergency visit rates for selected health conditions per 100,000 population for calendar year 2020. Emergency department visit rates are defined as the number of visits to emergency departments due to a certain condition, divided by the total population of the local geographic area. This figure is the part of "Alberta Health Primary Health Care - Community Profiles" report published August 2022.

This dashboard illustrates aggregated statistics on the status, actions, outcomes, and prosecutions from inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). This dashboard illustrates aggregated statistics on the status, actions, outcomes, and prosecutions from inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). The data is summarized on a quarterly basis, from 2016 to present. This dashboard will be updated on a quarterly basis with data from the Provincial Animal Welfare Program. The data table used for this dashboard reflects Manitoba Animal Welfare (AW) Program – Case Outcomes. The data table used for this dashboard is Manitoba Animal Welfare Program – Case Outcomes. There are two charts for this dashboard: Inspection Outcomes: This is a bar chart that ranks case outcomes from inspections conducted for assigned cases, in ascending order, for the user-selected time period. Prosecutions: This is a bar chart that ranks prosecution types associated with each assigned cases, in ascending order, for the user-selected time period. There are five indicators for this dashboard: Concerns Reported: This indicator displays the number of concerns reported for assigned cases in the user-selected time period. Inspections Conducted: This indicator displays the number of inspections conducted for assigned cases in the user-selected time period. Tickets Issued: This indicator displays the number of tickets issued for all assigned cases in a user-selected time period. Court Prosecutions: This indicator displays the number of court prosecutions for all assigned cases in the user-selected time period. Appeals Made: This indicator displays the number of appeals made for assigned cases in the user-selected time period. For more information, please refer to the Animal Welfare Main Page.

This dashboard shows aggregated statistics on non-compliances to five sections under The Animal Care Act, following inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). This dashboard shows aggregated statistics on non-compliances to five sections under The Animal Care Act following inspections conducted by the Manitoba Animal Welfare Program’s Animal Protection Officers (APO). Non-compliances to any of the five sections of the act, are represented by a bar on the chart. The number for each section is shown from 2016 to present. Data from this dashboard will be updated on a quarterly basis and all data come from the Provincial Animal Welfare Program. The data table used for this dashboard is Manitoba Animal Welfare Program – Non-Compliances to The Animal Care Act. There is one chart on this dashboard, a bar chart that ranks the number of non-compliances to any of the five sections under the act in ascending order for the user-selected time period of quarterly intervals, beginning in 2016, to the current quarter. For more information, please refer to the Animal Welfare Main Page.

Displays a bar chart showing either the number or rate of reported cases for a single disease or multiple diseases (up to 6) for any selected year from 1991 up to 2016 and is displayed by age group. The source data table, limitations of the data and descriptions of the selected notifiable disease(s) are also provided.

This publication series contains the accumulation measurements from stake farm Pegelfeld Süd on the Ekström Ice Shelf, Antarctica. The stake farm, located approximately 6 km to the southwest from the past and present Neumayer Station, has been in operation since December 1990. It consists of 16 aluminum poles (balise), placed in a grid of 4 x 4. Readings have been carried out in bi-weekly to monthly intervals by the overwintering staff of the air chemistry observatory (Spuso). Each data set in the series contains all measurements of each stake from one calendar year in a csv file, the average accumulation of the stake farm for each measurement and the standard deviation of the stake farm for each measurement. The data sets are accompanied by figures illustrating the development of the cumulative accumulation since the beginning of the measurements to date, a bar chart of the monthly accumulation for the year and a collection of panels (one panel per measurement) illustrating the variation of accumulation within the stake farm.

ADMIXTURE output (ancestry proportions) for 55 individuals for which we have whole genome sequences. Dataset was used to generate the plot in Figure 1D. Admixture proportions were simply plotted using a bar chart in R

This is the Web Map Server of DWD.:DWD and JMA (Japan Meteorological Agency) monitor the availability of monthly CLIMAT messages for the two measurement networks GSN (GCOS Surface Network) and RBCN (Regional Basic Climatological Network) on behalf of the WMO on the basis of monitoring products provided at www.gsnmc.dwd.de. From a selected station, the formats of the CLIMAT messages (BUFR or TAC) in the last 12 months are displayed in a bar chart.