seaborn-data | Data repository for seaborn examples

 by   mwaskom Python Version: Current License: No License

kandi X-RAY | seaborn-data Summary

kandi X-RAY | seaborn-data Summary

seaborn-data is a Python library typically used in Data Science, Tensorflow applications. seaborn-data has no bugs, it has no vulnerabilities and it has medium support. However seaborn-data build file is not available. You can download it from GitHub.

Data repository for [seaborn] examples. This repository exists only to provide a convenient target for the seaborn.load_dataset function to download sample datasets from. Its existence makes it easy to document seaborn without confusing things by spending time loading and munging data. The datasets may change or be removed at any time if they are no longer useful for the seaborn documentation. Some of the datasets have also been modifed from their canonical sources.

            kandi-support Support

              seaborn-data has a medium active ecosystem.
              It has 1214 star(s) with 2871 fork(s). There are 59 watchers for this library.
              It had no major release in the last 6 months.
              There are 2 open issues and 8 have been closed. On average issues are closed in 169 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of seaborn-data is current.

            kandi-Quality Quality

              seaborn-data has 0 bugs and 0 code smells.

            kandi-Security Security

              seaborn-data has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              seaborn-data code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              seaborn-data does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              seaborn-data releases are not available. You will need to build from source code and install.
              seaborn-data has no build file. You will be need to create the build yourself to build the component from source.
              seaborn-data saves you 43 person hours of effort in developing the same functionality from scratch.
              It has 152 lines of code, 7 functions and 9 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed seaborn-data and discovered the below as its top functions. This is intended to give you an instant insight into seaborn-data implemented functionality, and help decide if they suit your requirements.
            • The main function of the sampler
            • Return True if passenger is a child of male .
            Get all kandi verified functions for this library.

            seaborn-data Key Features

            No Key Features are available at this moment for seaborn-data.

            seaborn-data Examples and Code Snippets

            No Code Snippets are available at this moment for seaborn-data.

            Community Discussions


            Ifelse leaving other observations as is
            Asked 2021-Oct-28 at 18:38

            In R and tidy verse, there is a way to use ifelse() such that I can change several of the observations in a variable but then I can leave other observations that I don't want changed as they are but just setting else to that column (so in the example below, "Virginica and "Versicolor" would remain the same. Can't figure out how to do that in pandas.

            iris = pd.read_csv('')

            Minimal reproducible example:



            Answered 2021-Oct-28 at 18:31


            Method chaining with pandas function
            Asked 2021-Sep-07 at 14:35

            Why can't I chain the get_dummies() function?



            Answered 2021-Sep-07 at 14:17

            You can't chain the pd.get_dummies() method since it is not a pd.DataFrame method. However, assuming -

            1. You have a single column left after you drop your columns in the previous step in the chain.
            2. Your column is a string column dtype.

            ... you can use pd.Series.str.get_dummies() which is a series level method.



            Web scraping with selenium - 0 records returned
            Asked 2021-Aug-28 at 19:17

            I am working with this code for a long time to solve my problem and cannot find a solution for this. Using Selenium, I have first logged on to the site and doing scraping. But its returning 0 values, which is not expected.



            Answered 2021-Aug-28 at 16:11

            If you have "Login successful" then you need to replace:



            The property outliercolor of python plotly graph_objects box marker is not working (possible bug)
            Asked 2021-Jul-12 at 01:13

            I think I've found a bug in the class Marker, because the property outliercolor is not working. I followed the reference in, but it wont make any difference to change the outliers color.

            Here is an example:



            Answered 2021-Jul-12 at 01:13

            This does indeed appear to be a bug in Plotly - this can be submitted as a bug report to the Plotly team.

            It is worth noting that modifying boxpoints = "outliers" to boxpoints = "suspectedoutliers" produces markers with a different color so suspectedoutliers behaves as expected. However, you can't use suspectedoutliers in place of outliers as suspected outliers are only a subset of all outliers.

            You can achieve the desired behavior by plotting the outliers manually. To do this, you would still set boxpoints=outliers, but then plot the outliers as individual scatter points with the desired color over the outliers generated by Plotly.

            This is a bit intensive because this requires a rewrite of the algorithm to determine outliers exactly as the Plotly library performs this calculation. And unfortunately, you cannot extract Q1, Q3 or other statistics from go.Box or from Plotly in any way as these computations are performed by the Javascript under the hood when the figure renders.

            The first thing to note is that calculating Q1 and Q3 differs between different Python libraries: Plotly outlines their methods in the documentation, explaining that they use Method #10 in this short paper to calculate percentiles.

            In Python, the function to calculate percentiles using Method #10 (linear interpolation) looks like this:



            Round function to avoid error caused by null data
            Asked 2021-Jun-20 at 00:32




            • round data by my defined function like below.


            • When, it returns ValueError: cannot convert float NaN to integer.

            I don't want to split data into null data and changed the not null data and then merge it. But using one function to achieve it.



            Answered 2021-Jun-20 at 00:32

            Easiest fix would be to use np.ceil/np.floor which are both NaN safe:



            Statistical annotations in plotly bar graph
            Asked 2020-Dec-18 at 19:54

            What is a good way to create statistical annotations in plotly bar graphs? And how can I move the p-value in the figure below to the middle, i.e. between the two bar charts?

            Image of plotly graph with p-values



            Answered 2020-Dec-18 at 19:54

            Here's a solution using absolute text positioning (not zoomable).



            Create a category-code map based off a Dask.Series
            Asked 2020-Nov-16 at 19:09

            I have a Dask.Series with a categorical dtype that is known. I want to create a little dataframe which shows the associated mapping without having to compute the entire series. How do I achieve this?



            Answered 2020-Nov-16 at 19:09

            How about the following:



            How to input single variable at the last layer in keras?
            Asked 2020-Sep-29 at 09:48

            I am trying to include a variable in the last step of a feed-forward NN in Keras. I seem to only be able to get it working when I include 2 columns, instead of only one. Here's my code example:

            First I prepare my main input datasets:



            Answered 2020-Sep-29 at 09:48

            you simply have to specify correctly the input shape. In the case of 2D data, you need to pass only the feature dim. The sample dimension is not required. You simply need to correct the input into:



            Pandas pipeline with conditions
            Asked 2020-Jun-11 at 12:46

            I have a Pandas pipeline and would like to use either count or mean function based on a boolean variable.

            I came out with the following solution:



            Answered 2020-Jun-11 at 12:46

            Change to lambda and it seems to work fine:



            Trying to Plot with Seaborn: Error: InvalidURL: URL can't contain control characters. '/mwaskom/seaborn-data/master/
            Asked 2020-May-01 at 14:53

            I'm receiving the error: InvalidURL: URL can't contain control characters. '/mwaskom/seaborn-data/master/" when I try to plot a scatter plot with Seaborn

            Seaborn imported fine, without any errors. As did my dataset. While I feel the error doesn't have to do with my code, here's my code for the scatterplot, just in case.



            Answered 2020-May-01 at 14:53

            I'm glad you included your code!
            The function sns.load_dataset() gets data from the web.
            You don't need that here.
            So simply do this:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install seaborn-data

            You can download it from GitHub.
            You can use seaborn-data like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
          • HTTPS


          • CLI

            gh repo clone mwaskom/seaborn-data

          • sshUrl


          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link