panda | code powering the comma.ai panda

 by   commaai C Version: Current License: MIT

kandi X-RAY | panda Summary

kandi X-RAY | panda Summary

panda is a C library. panda has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

panda is the nicest universal car interface ever. It supports 3x CAN, 2x LIN, and 1x GMLAN. It also charges a phone. On the computer side, it has USB. It uses an STM32F413. It is 2nd gen hardware, reusing code and parts from the NEO interface board.
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            kandi-support Support

              panda has a medium active ecosystem.
              It has 1337 star(s) with 648 fork(s). There are 97 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 91 open issues and 179 have been closed. On average issues are closed in 119 days. There are 50 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of panda is current.

            kandi-Quality Quality

              panda has no bugs reported.

            kandi-Security Security

              panda has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              panda is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              panda releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

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            panda Key Features

            No Key Features are available at this moment for panda.

            panda Examples and Code Snippets

            No Code Snippets are available at this moment for panda.

            Community Discussions

            QUESTION

            Pandas: List of maximum values of difference from previous rows in new column
            Asked 2021-Jun-16 at 03:33

            I want to add a new column 'BEST' to this dataframe, which contains a list of the names of the columns which meet these criteria:

            • Subtract from the current value in each column the value in the row that is 2 rows back
            • The column that has the highest result of this subtraction will be listed in 'BEST'
            • If more more than one column shares the same highest result, they all get listed
            • If all columns have the same result, they all get listed

            Input:

            ...

            ANSWER

            Answered 2021-Jun-16 at 03:33

            First use shift and subtract to get the diff, then replace the maximum values with the column name and drop the others.

            Source https://stackoverflow.com/questions/67995888

            QUESTION

            repeat values of a column based on a condition
            Asked 2021-Jun-16 at 00:54

            I have a data frame including three columns named 'Altitude', 'Distance', 'Slope'. The column of 'Slope' is calculated using the two first columns 'Altitude', 'Distance'. @ the first step the purpose was to calculate 'Slope' using a condition explained below: A condition function was deployed to start from the top column of the "Distance" variable and add up (sum) values until the summation of them is greater or equal to 10 (>=10). If this condition corrects then calculate the "Slope" using the given formula: Slope=Average(Altitude)/(sum(Distance)). The summation of the 'Distance' was counting from the first value of that to the index that the 'Distance' has stopped there). The following code is for the above explanation (By Tim Roberts):

            ...

            ANSWER

            Answered 2021-May-19 at 13:38

            Use this code after you calculate s to get slope column with desired values:

            Source https://stackoverflow.com/questions/67602985

            QUESTION

            Identify distinct mappings of two overlapping columns in Pandas
            Asked 2021-Jun-15 at 20:56

            Suppose I have a Pandas dataframe with two identifier columns like this:

            ...

            ANSWER

            Answered 2021-Jun-15 at 20:56

            Sounds like a network issue, try with networkx

            Source https://stackoverflow.com/questions/67993365

            QUESTION

            drop a level two column from multi index dataframe
            Asked 2021-Jun-15 at 20:39

            Consider this dataframe:

            ...

            ANSWER

            Answered 2021-Jun-15 at 20:30

            QUESTION

            Create new columns based on rank order in Pandas
            Asked 2021-Jun-15 at 19:02

            I have a data frame like this,

            ...

            ANSWER

            Answered 2021-Jun-11 at 05:56
            df = df.set_index(["ID", "Rank"])
            df = df.unstack("Rank")
            df.columns = df.columns.map(lambda col: "_".join(map(str, col)))
            

            Source https://stackoverflow.com/questions/67931685

            QUESTION

            Filter dictionary whose values are arrays
            Asked 2021-Jun-15 at 18:35

            I have data which looks like this:

            ...

            ANSWER

            Answered 2021-Jun-15 at 18:35
            import numpy as np
            
            features_dict = {
                'feat1': np.array([[0,1],[2,3],[4,5]]), 
                'feat2': np.array([[6,7],[8,9],[10,11]]),
                'feat3': np.array([1, 0, 0]),
                'feat4': np.array([[1],[2],[1]])
            }
            
            ind = features_dict['feat3'] == 0
            features_dict = {k: v[ind] for k,v in features_dict.items()}
            

            Source https://stackoverflow.com/questions/67991514

            QUESTION

            Check Graph Reciprocity using Pandas
            Asked 2021-Jun-15 at 18:22

            I have a Graph loaded in pandas and I want to check if my graph has nodes with reciprocity. My dataset looks like this:

            id from to 0 s01 s03 1 s02 s01 2 s03 s01

            The desired output of my code is the reciprocal nodes: (s01, s03)

            I found a solution transforming my dataframe into tuples and comparing each combination of my nodes, but I'm sure this solution is far from ideal. Following is my code:

            ...

            ANSWER

            Answered 2021-Jun-15 at 18:22

            You can merge the DataFrame with itself after swapping the from and to columns in the right DataFrame. Then sort the merged result and drop duplicates to get the unique pairs of reciprocal nodes.

            Source https://stackoverflow.com/questions/67991543

            QUESTION

            Parsing XML using Python and create an excel report - Elementree/lxml
            Asked 2021-Jun-15 at 17:46

            I am trying to parse many XML test results files and get the necessary data like testcase name, test result, failure message etc to an excel format. I decided to go with Python.

            My XML file is a huge file and the format is as follows. The cases which failed has a message, & and the passed ones only has . My requirement is to create an excel with testcasename, test status(pass/fail), test failure message.

            ...

            ANSWER

            Answered 2021-Jun-15 at 17:46

            Since your XML is relatively flat, consider a list/dictionary comprehension to retrieve all child elements and attrib dictionary. From there, call pd.concat once outside the loop. Below runs a dictionary merge (Python 3.5+).

            Source https://stackoverflow.com/questions/67977767

            QUESTION

            Pandas RMSE Groupby Multiple Conditions
            Asked 2021-Jun-15 at 17:13

            I am trying to compute the RMSE of a panda dataframe based on multiple conditions: (plant_name, year, month). My datafram (df3m) looks like this:

            ...

            ANSWER

            Answered 2021-Jun-15 at 17:13

            You can use .GroupBy.apply() and put the call to mean_squared_error inside it, as follows:

            Source https://stackoverflow.com/questions/67990261

            QUESTION

            How to slice on values instead of index
            Asked 2021-Jun-15 at 17:04

            I have this panda series

            ...

            ANSWER

            Answered 2021-Jun-15 at 17:04

            You should set the mydata index to True.

            Source https://stackoverflow.com/questions/67990414

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

            Vulnerabilities

            No vulnerabilities reported

            Install panda

            You can download it from GitHub.

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