Write a function to convert given CSV file to Dataframe
Define function with name csv_to_dataframe which should accept filepath as a parameter.
Function should return a dataframe.
As we require a dataframe, type of return variable should be pandas dataframe.
In case if we pass filepath which does not exist, function should raise FileNotFoundError.
Question 2
Write a function to convert datatype of given variables to "category"
Define function with name dtype_category which should accept dataframe and list of columns as parameters.
Function should return a dataframe with type of given columns changed to "category".
As we require a dataframe, type of return variable should be pandas dataframe.
In case if we pass column name which does not exist, function should raise KeyError
Question 3
Write a function to count number of "categorical variables"
Define function with name categorical_variable_count which should accept dataframe as parameter.
Function should return count of categorical variables.
As we require count, type of return variable should be integer.
In case if we pass dataframe which does not exist, function should raise NameError
Question 4
Write a function to check variance of numeric columns of a dataframe, and if variance is lower than given threshold, drop the column
Define function with name var_ckeck which should accept dataframe, threshold (int) as parameter.
Function should drop the the rejected columns and return a list of dropped variables.
As we require list, type of return variable should be list.
Question 5
Write a function to plot Q-Q plots of all numeric variables
Define function with name q_q_plot which should accept dataframe, column_list (of variables to be plotted) as parameters.
Function should return plots of numeric variables.
As we require plot, type of return variable should be matplotlib object.
In case if we pass column name which does not exist, function should raise KeyError
Question 6
Write a function to build a Logistic Regression model
Define function with name logistic_regression_model which should accept dataframe, dependent_variable (as string) and independent_variable_list (as a list of columns) as parameters.
Function should return accuracy of the model in %.
As we require accuray, type of return variable should be numeric.
In case if we pass column name which does not exist or is not numerical type, function should raise KeyError
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