yasDataPrepKit 0.4.0

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how to use this package:

#after you download the package from PyPi

#to import this package import YasinDataPrepKit as dtk

#your can read a csv, json and Excel files and in order to do #that your need to do the next:

#first you need to make an object and call the ReadingData class obj = dtk.ReadingData(r”Your file absolute path”)

#make sure to always use (r””)when reading your data for #correctly read your file path

#after this your call the read() function like this obj.read()

#after you have done these steps correctly then the rest is easy #you can do many function for data summary for instance:

#to find mean of int and float columns you use print(obj.calculate_mean())

#to find the maximum print(obj.max_value())

#for handling missing values you can use either the remove or #impute methods print(obj.handle_missing_values(‘remove’)) print(obj.handle_missing_values(‘impute’))

#the ‘remove’ and ‘impute’ is you specifying the strategy you #want to use to handle missing values

#there is also a function for encoding using one hot encoding print(obj.encode_categorical_data())

#here is a list for all functions other than the ones above that you can use from this package

#to calculate sum print(obj.calculate_sum())

#to calculate minimum print(obj.min_value())

#to calculate median print(obj.median_value())

#to calculate variance print(obj.var_value())

#to calculate standard deviation print(obj.std_deviation())

#to calculate correlation coefficient print(obj.cor_coefficient())