Skip to main content
SimilarExport ZIP
100%

All Uber Trips in NYC from 08/01/2014 to 08/14/2014

✓ Published0🌍 Public
Llokesh234
Last edited Sep 24, 2020
Created on Sep 8, 2020

This visualization displays basic metadata about all Uber trips in New York City from August 1–14, 2014, reporting the file size in kilobytes, row count, and column count of the source dataset. The page loads a CSV from the FiveThirtyEight GitHub repository using `d3.csv` and then uses `d3.csvFormat` to calculate the raw data size, while reading `data.length` and `data.columns.length` to summarize the table. The results are rendered as large text in a `<pre>` element, with no graphical chart or map shown. The example demonstrates straightforward CSV loading and summary reporting with D3 v5.

AI-generated description

This dataset contains information about Uber Trips in NYC from 08/01/2014 to 08/14/2014. This is 'UberTripsNYC' dataset. Originally published at UberTripsNYC Data-Set.

MIT Licensed

Similar vizzes

Loading thumbnail…

2024 Uber Data

This visualization presents raw, unprocessed ride data from Uber throughout 2024, displaying each trip's attributes such as date, time, vehicle type, pickup and drop locations, booking value, ride distance, and ratings. The code fetches a CSV file, parses it using `csvParse`, and converts specific quantitative fields—including `avg_vtat`, `booking_value`, and `ride_distance`—to numeric types. Built with the D3.js v7 library, the visualization uses a `select().join()` pattern to render the JSON representation of the dataset within a `<pre>` element, showing the structured data without additional graphical encoding.

BBen Trantanella
79% match
Loading thumbnail…

Fork of yasmeen

This page displays metadata for a New York Uber Cab Dataset, including the file size in kilobytes, the number of rows, and the number of columns. The visualization is minimal, presenting this information as plain text within an HTML page styled with CSS, featuring a cab background image. The code uses the `d3.csv` API to fetch the dataset from a remote URL and `d3.csvFormat` to compute its size, then writes the summary into a `<pre>` element. The page also provides a link to view the raw CSV data.

SSravaniPosina
73% match
Loading thumbnail…

q3

This interactive scatter plot visualizes New York City taxi trip data, showing trip distance against pickup hour. Each circle represents a trip, colored by the day of the week, with a color legend that filters data on hover. The visualization uses React with D3 scales (`scaleLinear`, `scaleOrdinal`) to render SVG elements. The `csv` loader fetches data from a remote gist, while interactive hovering triggers opacity fading for non-selected categories.

UUmarani Vemula
70% match
Loading thumbnail…

D3 Heatmap

This heatmap visualizes the number of Uber rides per month and year, with months on the x-axis, years on the y-axis, and color intensity encoding ride counts. It uses d3.csv to load the dataset, d3.scaleBand for both axes, and d3.scaleSequential with a color interpolator to map counts to cell colors. The SVG is rendered with d3.axisBottom and d3.axisLeft, while cells are drawn as rects. Data is aggregated client-side by parsing timestamps into month-year pairs.

DDominic Fernandez
70% match
Loading thumbnail…

D3 Scatterplot

This interactive D3 scatterplot visualizes cumulative Uber fare amounts per day from 2009 to 2015, using data from a Kaggle dataset. The SVG chart plots each date on the x-axis and total daily fares on the y-axis, with green circles marking individual points. The visualization uses `d3.csv` to load the raw data, `d3.scaleBand` for the time-based x-axis, and `d3.scaleLinear` for the fare amounts. Custom tick marks highlight the first date of each year, while gridlines and labeled axes improve readability.

DDominic Fernandez
69% match
Loading thumbnail…

Dot Plot

This dot plot shows the number of Uber rides per year, with each circle representing a year’s total ride count positioned along a horizontal axis scaled by increments of 2,000 rides. The visualization aggregates data from a CSV file loaded via p5.js’s `loadTable` function, then uses `createCanvas` and `circle` to render the points. Year labels appear along a vertical axis, and ride counts are formatted using a custom `kFormatter` function for values above 1,000. The plot excludes 2008 data and displays results across a 625×625 pixel canvas.

DDominic Fernandez
68% match
Loading thumbnail…

Bar Chart

This bar chart visualizes the total Uber fare amount per year, drawing on a CSV dataset of ride records. The visualization excludes 2008 data and sums the fares for each remaining year, displaying the results as a series of teal bars. The chart is rendered using the p5.js library, which loads the data with `loadTable`, processes it within the `draw` loop, and creates the visual elements. Custom functions like `kFormatter` are used to format large numbers with a "k" suffix on the y-axis, which is labeled "Fare Amount."

DDominic Fernandez
68% match
Loading thumbnail…

Nwe York Airbnb

This example displays a plain-text summary of a New York Airbnb dataset, showing the file size in kilobytes, the number of rows, and the number of columns. It loads the data from a CSV file hosted on GitHub using `d3.csv`, then writes the calculated values into a `<pre>` element via `document.getElementById`. The implementation relies on `d3.csvFormat` to measure the raw data length and `d3.csvParse` (shown in the commented alternative) for parsing. The page uses D3 v5 and no other visualization libraries or rendering techniques.

XXinting Yao
67% match