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0001 {
0002 "name": "seaborn",
0003 "categories": [
0004 {
0005 "name": "Misc",
0006 "subcategories": [
0007 {
0008 "datasets": [
0009 {
0010 "description": "One of the example datasets used in the course \"PSYCH 252: Statistical Methods\". <br><br>Source: https://psych252.github.io/",
0011 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/anagrams.csv",
0012 "filename": "anagrams",
0013 "name": "Anagrams",
0014 "use_first_row_for_vectorname": true
0015 },
0016 {
0017 "description": "Anscombe's quartet comprises four data sets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed. Each dataset consists of eleven (x,y) points. They were constructed in 1973 by the statistician Francis Anscombe to demonstrate both the importance of graphing data when analyzing it, and the effect of outliers and other influential observations on statistical properties. He described the article as being intended to counter the impression among statisticians that \"numerical calculations are exact, but graphs are rough.\". <br><br>Source: https://en.wikipedia.org/wiki/Anscombe%27s_quartet",
0018 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/anscombe.csv",
0019 "filename": "anscombe",
0020 "name": "Anscombe's quartet",
0021 "use_first_row_for_vectorname": true
0022 },
0023 {
0024 "description": "One of the example datasets used in the course \"PSYCH 252: Statistical Methods\". <br><br>Source: https://psych252.github.io/",
0025 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/attention.csv",
0026 "filename": "attention",
0027 "name": "Attention",
0028 "use_first_row_for_vectorname": true
0029 },
0030 {
0031 "description": "Brane Networks",
0032 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/brain_networks.csv",
0033 "filename": "brain_networks",
0034 "name": "Brain Networks",
0035 "use_first_row_for_vectorname": true
0036 },
0037 {
0038 "description": "This dataset contains data behind the story \"Dear Mona, Which State Has The Worst Drivers?\". <br><br>Source: http://fivethirtyeight.com/datalab/which-state-has-the-worst-drivers/",
0039 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/car_crashes.csv",
0040 "filename": "car_crashes",
0041 "name": "FiveThirtyEight Bad Drivers Dataset",
0042 "use_first_row_for_vectorname": true
0043 },
0044 {
0045 "description": "A dataset containing the prices and other attributes of almost 54,000 diamonds. <br><br>Source: https://ggplot2.tidyverse.org/reference/diamonds.html",
0046 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv",
0047 "filename": "diamonds",
0048 "name": "Diamonds",
0049 "use_first_row_for_vectorname": true
0050 },
0051 {
0052 "description": "Data taken from the publication \"Roitman, JD and Shadlen, MN (2002), Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task, Journal of Neuroscience, Vol. 22(21), 9475-9489\". <br><br>Source: https://shadlenlab.columbia.edu/resources/RoitmanDataCode.html",
0053 "url": "https://github.com/mwaskom/seaborn-data/raw/master/dots.csv",
0054 "filename": "dots",
0055 "name": "Dots",
0056 "use_first_row_for_vectorname": true
0057 },
0058 {
0059 "description": "Dow-Jones Industrial Stock Price Index for United States taken from the National Bureau of Economic Research. <br><br>Source: https://fred.stlouisfed.org/series/M1109BUSM293NNBR",
0060 "url": "https://github.com/mwaskom/seaborn-data/raw/master/dowjones.csv",
0061 "filename": "dowjones",
0062 "name": "Dow-Jones Industrial Stock Price Index for United States",
0063 "use_first_row_for_vectorname": true
0064 },
0065 {
0066 "description": "One of the example datasets used in the course \"PSYCH 252: Statistical Methods\". <br><br>Source: https://psych252.github.io/",
0067 "url": "https://github.com/mwaskom/seaborn-data/raw/master/exercise.csv",
0068 "filename": "exercise",
0069 "name": "Exercise",
0070 "use_first_row_for_vectorname": true
0071 },
0072 {
0073 "description": "Flights.",
0074 "url": "https://github.com/mwaskom/seaborn-data/raw/master/flights.csv",
0075 "filename": "flights",
0076 "name": "Flights",
0077 "use_first_row_for_vectorname": true
0078 },
0079 {
0080 "description": "Data taken from the publication \"Waskom, M.L., Frank, M.C., Wagner, A.D. (In Press). Adaptive engagement of cognitive control in context-dependent decision-making. Cerebral Cortex.\". <br><br>Source: https://github.com/mwaskom/Waskom_CerebCortex_2017",
0081 "url": "https://github.com/mwaskom/seaborn-data/raw/master/fmri.csv",
0082 "filename": "fmri",
0083 "name": "Functional magnetic resonance imaging",
0084 "use_first_row_for_vectorname": true
0085 },
0086 {
0087 "description": "Waiting time between eruptions and the duration of the eruption for the Old Faithful geyser in Yellowstone National Park, Wyoming, USA. <br><br>Source: https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/faithful.html",
0088 "url": "https://github.com/mwaskom/seaborn-data/raw/master/geyser.csv",
0089 "filename": "geyser",
0090 "name": "Old Faithful Geyser Data",
0091 "use_first_row_for_vectorname": true
0092 },
0093 {
0094 "description": "Results of the Glue Benchmark Leaderboard. <br><br>Source: https://gluebenchmark.com/leaderboard/",
0095 "url": "https://github.com/mwaskom/seaborn-data/raw/master/glue.csv",
0096 "filename": "glue",
0097 "name": "Glue Benchmark Leaderboard",
0098 "use_first_row_for_vectorname": true
0099 },
0100 {
0101 "description": "Health financing is reported as the annual per capita health expenditure and is adjusted for inflation and price level differences between countries (measured in 2010 international dollars). <br><br>Source: https://ourworldindata.org/grapher/life-expectancy-vs-health-expenditure",
0102 "url": "https://github.com/mwaskom/seaborn-data/raw/master/healthexp.csv",
0103 "filename": "healthexp",
0104 "name": "Life expectancy vs. health expenditure, 2015",
0105 "use_first_row_for_vectorname": true
0106 },
0107 {
0108 "description": "A small classic dataset from Fisher, 1936. One of the earliest known datasets used for evaluating classification methods. This is one of the earliest datasets used in the literature on classification methods and widely used in statistics and machine learning. The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are not linearly separable from each other. <br><br>Source: https://archive.ics.uci.edu/dataset/53/iris",
0109 "url": "https://github.com/mwaskom/seaborn-data/raw/master/iris.csv",
0110 "filename": "iris",
0111 "name": "Iris",
0112 "use_first_row_for_vectorname": true
0113 },
0114 {
0115 "description": "A dataset for cars and their associated price & features; manufactured between 1970-82 in USA, Europe., and Japan. <br><br>Source: https://data.world/dataman-udit/cars-data",
0116 "url": "https://github.com/mwaskom/seaborn-data/raw/master/mpg.csv",
0117 "filename": "mpg",
0118 "name": "Cars Dataset",
0119 "use_first_row_for_vectorname": true
0120 },
0121 {
0122 "description": "The goal of this dataset is to provide a great dataset for data exploration & visualization, as an alternative to iris. <br><br>Source: https://github.com/allisonhorst/palmerpenguins",
0123 "url": "https://github.com/mwaskom/seaborn-data/raw/master/penguins.csv",
0124 "filename": "penguins",
0125 "name": "Palmer Penguins",
0126 "use_first_row_for_vectorname": true
0127 },
0128 {
0129 "description": "Known planet discoveries beyond our solar system. <br><br>Source: https://exoplanets.nasa.gov/discovery/exoplanet-catalog/",
0130 "url": "https://github.com/mwaskom/seaborn-data/raw/master/planets.csv",
0131 "filename": "planets",
0132 "name": "Planets",
0133 "use_first_row_for_vectorname": true
0134 },
0135 {
0136 "description": "Arctic and Antarctic sea ice data. <br><br>Source: https://nsidc.org/arcticseaicenews/sea-ice-tools/",
0137 "url": "https://github.com/mwaskom/seaborn-data/raw/master/seaice.csv",
0138 "filename": "seaice",
0139 "name": "Arctic and Antarctic sea ice",
0140 "use_first_row_for_vectorname": true
0141 },
0142 {
0143 "description": "TLC Trip Record Data. <br><br>Source: https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page",
0144 "url": "https://github.com/mwaskom/seaborn-data/raw/master/taxis.csv",
0145 "filename": "taxis",
0146 "name": "TLC Trip Record Data",
0147 "use_first_row_for_vectorname": true
0148 },
0149 {
0150 "description": "One waiter recorded information about each tip he received over a period of a few months working in one restaurant. <br><br>Source: https://rdrr.io/cran/reshape2/man/tips.html",
0151 "url": "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv",
0152 "filename": "tips",
0153 "name": "Tipping data.",
0154 "use_first_row_for_vectorname": true
0155 },
0156 {
0157 "description": "Titanic passengers data. <br><br>Source: https://www.kaggle.com/c/titanic/data.",
0158 "url": "https://github.com/mwaskom/seaborn-data/raw/master/titanic.csv",
0159 "filename": "titanic",
0160 "name": "Titanic",
0161 "use_first_row_for_vectorname": true
0162 }
0163 ],
0164 "name": "Misc"
0165 }
0166 ]
0167 }
0168 ]
0169 }