def export_normal_distribution(self, column, date):
path = DataFrame.get_export_path(date)
mean = MathsUtil.arr_mean(self.data[self.headers[column]])
median = MathsUtil.arr_median(self.data[self.headers[column]])
mode = MathsUtil.arr_mode(self.data[self.headers[column]])
GraphUtils.export_distribution_graph(self.data[self.headers[column]], self.headers[column],
mean, median, mode, path)
print(f"exported {path}dist_{self.headers[column]}")
def plot_normal_distribution(self, column):
mean = MathsUtil.arr_mean(self.data[self.headers[column]])
median = MathsUtil.arr_median(self.data[self.headers[column]])
mode = MathsUtil.arr_mode(self.data[self.headers[column]])
GraphUtils.show_distribution_graph(self.data[self.headers[column]], self.headers[column], mean, median, mode)
def print_deviation_calculations(self, column):
rows = self.data[self.headers[column]]
DataFrame.print_deviation_calculation("Mean", rows, MathsUtil.arr_mean(rows))
DataFrame.print_deviation_calculation("Median", rows, MathsUtil.arr_median(rows))
DataFrame.print_deviation_calculation("Mode", rows, MathsUtil.arr_mode(rows))
