data_analysis | Source codes involved in data analysis | Data Visualization library

 by   sparkandshine Python Version: Current License: GPL-3.0

kandi X-RAY | data_analysis Summary

kandi X-RAY | data_analysis Summary

data_analysis is a Python library typically used in Analytics, Data Visualization applications. data_analysis has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However data_analysis build file is not available. You can download it from GitHub.

Source codes involved in data analysis.
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            kandi-support Support

              data_analysis has a low active ecosystem.
              It has 19 star(s) with 10 fork(s). There are 5 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              data_analysis has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of data_analysis is current.

            kandi-Quality Quality

              data_analysis has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              data_analysis is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              data_analysis releases are not available. You will need to build from source code and install.
              data_analysis has no build file. You will be need to create the build yourself to build the component from source.
              data_analysis saves you 132 person hours of effort in developing the same functionality from scratch.
              It has 331 lines of code, 28 functions and 6 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed data_analysis and discovered the below as its top functions. This is intended to give you an instant insight into data_analysis implemented functionality, and help decide if they suit your requirements.
            • C crawler s Chinese IDU
            • Return a list of idioms
            • Format a list of Chineseidioms
            • Retrieve unregistered domains
            • Format a list of domain names to file
            • Given a list of domain names return a list of domain names
            • Get contact info
            • Get all contact URLs
            • Print a list of lists
            • Get a list of values from a worksheet
            • Format contact infos
            • Generate domain names
            • Read a worksheet into a list of lists
            • Read a CSV file into a list of lists
            • Opens a spreadsheet sheet
            • Extract a column from a list of lists
            Get all kandi verified functions for this library.

            data_analysis Key Features

            No Key Features are available at this moment for data_analysis.

            data_analysis Examples and Code Snippets

            No Code Snippets are available at this moment for data_analysis.

            Community Discussions

            QUESTION

            my code is ugly: extracting only the files I want from a list of files
            Asked 2021-Mar-15 at 21:37

            My code gets the job done but it is ugly, too long and clumsy. I have to work through several thousand files which fall into 4 groups and I only want one specific type

            I want: '.docx'

            I do not want: '.pdf', 'SS.docx', or 'ss.docx'

            I tried several if not but they did not really work. In the end I built lists of all file types and the anti-join them to the complete list one after another so that only the files I am interested remain.

            Question:

            is it possible to simplify my if elif block? Could this be done with less lines to directly get to only the files I need?

            is it possible to pack the df generation into a loop instead of having to do it manually for each?

            ...

            ANSWER

            Answered 2021-Mar-15 at 21:37

            Since you:

            • Only want '.docx' (i.e. as determined by suffix)
            • Do not want: '.pdf', 'SS.docx', or 'ss.docx' (i.e. fies with these endings)

            This could be done more simply as follows.

            Code--Option 1 using str endswith

            Source https://stackoverflow.com/questions/66642610

            QUESTION

            overflow:scroll; property is not providing enough scroll depth
            Asked 2021-Jan-13 at 07:36

            CSS overflow:scroll; property doesn't provide large scrolling depth. Unable to see the hidden data as scrollbar doesn't scroll enough.

            My github link for the code is below. https://github.com/krishnasai3cks/portfolio

            ...

            ANSWER

            Answered 2021-Jan-13 at 07:36

            Removing the display: flex property from this class will fix it.

            Source https://stackoverflow.com/questions/65697207

            QUESTION

            "OverflowError: Python int too large to convert to C long" when running a RandomizedSearchCV with scipy distributions
            Asked 2020-Nov-18 at 21:17

            I want to run the following RandomizedSearch:

            ...

            ANSWER

            Answered 2020-Nov-18 at 21:17

            I don't see an alternative to dropping RandomizedSearchCV. Internally RandomSearchCV calls sample_without_replacement to sample from your feature space. When your feature space is larger than C's long size, scikit-learn's sample_without_replacement simply breaks down.

            Luckily, random search kind of sucks anyway. Check out optuna as an alternative. It is way smarter about where in your feature space to spend time evaluating (paying more attention to high-performing areas), and does not require you to limit your feature space precision beforehand (that is, you can omit the step size). More generally, check out the field of AutoML.

            If you insist on random search however, you'll have to find another implementation. Actually, optuna also supports a random sampler.

            Source https://stackoverflow.com/questions/64901096

            QUESTION

            How do I display Y values above the bars in a matplotlib barchart?
            Asked 2020-Jul-26 at 14:04

            I am generating a bar chart from a dataframe, I want to remove the Y axis labels and display them above the bars. How can I achieve this?
            This is my code so far:

            ...

            ANSWER

            Answered 2020-Jul-26 at 14:04

            using ax.patches you can achieve it.

            This will do:

            Source https://stackoverflow.com/questions/63100383

            QUESTION

            Not able to create Hive table with TIMESTAMP datatype in Azure Databricks
            Asked 2020-Jun-21 at 16:21

            org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.UnsupportedOperationException: Parquet does not support timestamp. See HIVE-6384;

            Getting above error while executing following code in Azure Databricks.

            ...

            ANSWER

            Answered 2020-Jun-21 at 13:39

            As per Hive-6384 Jira, Starting from Hive-1.2 you can use Timestamp,date types in parquet tables.

            Workarounds for Hive < 1.2 version:

            1. Using String type:

            Source https://stackoverflow.com/questions/62494705

            QUESTION

            Group nltk.FreqDist output by first word (python)
            Asked 2020-Jun-11 at 15:27

            I'm an amateur with basic coding skills in python, I'm working on a data frame that has a column as below. The intent is to group the output of nltk.FreqDist by the first word

            What I have so far

            ...

            ANSWER

            Answered 2020-Jun-11 at 07:51

            Try the following (documentation is inside the code):

            Source https://stackoverflow.com/questions/62317725

            QUESTION

            error missing 1 required positional argument python and thread
            Asked 2020-Apr-28 at 09:07

            I tried to use thread to get better run-time result for some reasons the error

            Missing 1 required positional argument: year is keeping popping on the screen

            here is the function:

            ...

            ANSWER

            Answered 2020-Apr-28 at 06:15

            Not really sure how your whole construct looks like, but the following should work...

            Source https://stackoverflow.com/questions/61473585

            QUESTION

            Creating a subplot of "combo" plots (hist + boxplot)
            Asked 2020-Mar-20 at 00:58

            I have this code:

            ...

            ANSWER

            Answered 2020-Mar-20 at 00:58

            I believe you can accomplish what you want using GridSpec. The following code should produce what you want using simulated data:

            Source https://stackoverflow.com/questions/60766265

            QUESTION

            TypeError: () got an unexpected keyword argument 'axis' when using an apply followed by a groupby
            Asked 2020-Mar-05 at 15:15

            Am trying to extract values from a pandas Dataframe which are split by an ID. However when I feed the apply groupby, it wont let me provide an axis argument to apply the function row wise

            ...

            ANSWER

            Answered 2020-Mar-05 at 15:15

            I had a similar error. I found that the apply function of a GroupBy object does not behave the same as the apply function of a Pandas DataFrame. More information on the apply function of the GroupBy object can be found here.

            The function you provide in your apply function should get dataframe as an argument. It also returns a dataframe. The function thus modifies a dataframe whereas the function you provided modifies a row.

            It gives the error () got an unexpected keyword argument 'axis' as the apply function here only accepts a function which modifies a dataframe and args kwargs which are fed to your function.

            It tries to feed your lambda function the axis parameter (which it thinks is an argument for your function) and since your lambda function does not demand this parameter, it displays this error.

            The solution for your end would be to change the lambda function to a correct function as described above.

            Source https://stackoverflow.com/questions/55537881

            QUESTION

            FileNotFoundError: [Errno 2] File b'smallsample.csv' does not exist: b'smallsample.csv'
            Asked 2019-Oct-07 at 02:54

            In Google Colab, I mounted google drive:

            ...

            ANSWER

            Answered 2019-Oct-07 at 02:54

            Assignin path = ... doesn't change the current working directory. Instead, use the absolute path as suggested by Michael, or change the working directory using:

            %cd /content/gdrive/My Drive

            You can observe the current working directory using %pwd and the files in the current directory using %ls.

            Source https://stackoverflow.com/questions/58262731

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

            Vulnerabilities

            No vulnerabilities reported

            Install data_analysis

            You can download it from GitHub.
            You can use data_analysis 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.

            Support

            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 .
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