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Parkinsons-Disease-Detection-Model

Machine learning project

import all required libraries

1)read the data using read_csv command of pandas Note:we can read .data file using same command that is raed_csv

2)frame the data for better reprenstation

3).head() command will print 1st five rows

4).shape will give the number of rows and number of coloums

 -number of rows represents number of patients
 -number of coloums represent the number of features 

5).info() will give you the how many non values are there in given coloums

-there are no null values in our dataset hence noNull count of each coloum of dataset is 195

6)similarly .isnull().sum() give the count of null values in dataset

7).describe()

-it will give you

1)count\n
2)mean
3)standard deviation
4)minimum value of each coloum
5)25% values are less than  reading  n of each coloum
6)50% values are less than  reading n of each coloum
7)75% values are less than  reading n of each coloum
8)maximum reading of each coloum
  1. .value_counts() will give the number of patient with parkinson and patient with no parkinson

9).drop(columns()) will drop the coloums which are not required for training

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