if isinstance(value, list):
data = [key if d in value else d for d in data if d]
unique_values = np.unique(np.array(data))
print(unique_values)
plot_data = dict()
for item in unique_values:
plot_data[item] = 0
if 'Not Disclosed' in plot_data.keys():
plot_data.pop('Not Disclosed')
plot_data['Not Disclosed'] = 0
for item in data:
if isinstance(item, float) and math.isnan(item):
plot_data['Not Disclosed'] += 1
else:
plot_data[item] += 1
self.plot_data = plot_data
if __name__ == '__main__':
# Load Data #
df = pd.read_csv("../Data/MainData.csv")
temp_headers = rename_header(df)
controller = FigureController(df)
controller.process_data(**temp_headers)
controller.draw_figure_bar_horizontally(save=True, height=0.25, exclude_fields=['Not Disclosed'])
for item in self.dataframe['professional_experience'].tolist():
if isinstance(item, float) and math.isnan(item):
plot_data['Not Disclosed'] += 1
else:
plot_data[item] += 1
self.plot_data = plot_data
def draw_figure(self, save=False, **kwargs):
objects = self.plot_data.keys()
age = np.arange(len(objects))
age_frequency = self.plot_data.values()
age_frequency = [
af * 100 / self.num_of_respondents for af in age_frequency
]
plt.bar(age, age_frequency, width=0.5, align='center', alpha=0.5)
plt.xticks(age, objects)
plt.xticks(rotation=90)
super(AgeFigureController, self).draw_figure(save=save)
if __name__ == '__main__':
# Load Data #
df = pd.read_csv("../Data/MainData.csv")
rename_header(df)
controller = AgeFigureController(df)
controller.process_data()
controller.draw_figure(save=True)
