PUBG DataSet Analysis with Pandas

Very basic level analysis with pubg dataset could be done by me with some junior level knowledge on pandas library

Dataset Link : PUBG DATASET

Dataset Analysis : Analysis on DATASET

Hierarchical indexing in pandas

Hierarchical indexing is an important feature of pandas enabling you to have multiple (two or more) index level on axis.  Somewhat abstractly , it provides a way for you to work with higher dimensional data in  lower dimensional form.

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Simple application on Iris flower

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Reindex function in Pandas

=> A critical method on pandas object is reindex .

=> Which means to create a new object with the data confirmed to a new index .

=> Introducing missing values if any index values were not already present :

 

Random Walks example Using Numpy module

An illustrative application of utilizing array operation is in the simulation of random walks. Let's first consider a simple random walks starting at 0 with steps of 1 and -1 occurring with equal probability.   

                    The walk is simply the cumulative sum of the random steps and could be evaluated as an array expression. Thus, I use the np.random module to draw 1000 coin flips at once ,set these to 1 to -1, and compute the cumulative sum :

 

meshgrid and where functions in Numpy

meshgrid () :-

     => It takes two 1D arrays and produces two 2D matrices corresponding to all pairs for (x,y) in             the two arrays.

            

where () :-

    => The numpy.where() function is a vectorized version of the ternary expression .

                ex : x if condition else y .

            

            

    

Fancy Indexing in Numpy

         => Fancy indexing is a term adopted by Numpy to describe indexing using integer arrays.

         => To select out a subset of the rows in a particular order .

         => You can pass either list or array of elements .

         => It also supports negative indices select rows from the end .