add demografic

Author: ayin21

bitbots_misc/bitbots_education/scripts/demografic.py

@@ -0,0 +1,56 @@
+import pandas as pd
+
+
+class Demographic:
+    def __init__(self, data, column_name):
+        
+        self.data = data
+        self.column_name = column_name
+        self.demographic_data = None
+        self.evaluateDemographics()
+
+    def evaluateDemographics(self):
+        demographic_list = []
+        for row in self.data:
+            demographic = self.getDemographicFromRow(row)
+            demographic_list.append(demographic)
+
+        self.demographic_data = pd.Series(demographic_list, name="Demographic Score")
+
+    def getDemographicFromRow(self, row):
+        demographic = 0
+        print(row)
+        match row:
+            case "A1":
+                demographic = 1
+            case "A2":
+                demographic = 2
+            case "A3":
+                demographic = 3
+            case "A4":
+                demographic = 4
+            case "A5":
+                demographic = 5
+            case "A6":
+                demographic = 6
+            case "A7":
+                demographic = 7
+
+        if (demographic == 0):
+            match row:
+                case "AO01":
+                    demographic = 1
+                case "AO02":
+                    demographic = 2
+                case "AO03":
+                    demographic = 3
+                case "AO04":
+                    demographic = 4
+                case "AO05":
+                    demographic = 5
+                case "AO06":
+                    demographic = 6
+                case "AO07":
+                    demographic = 7
+
+        return demographic

bitbots_misc/bitbots_education/scripts/study_evaluation.py

@@ -4,6 +4,7 @@
 import sus_score as ss
 import ios_score as io
 import ueq_score as ue
+import demografic as dm
 import log_evaluation as le
 import scipy.stats as stats
 import matplotlib.pyplot as plt
@@ -391,9 +392,10 @@ def calculate_significance(self, data1, data2, is_within_subject):
     evaluation.descriptive_data.to_csv("descriptive_data.csv")
     #evaluation.descriptive_log_data.to_csv("descriptive_log_data.csv")
 
-
+    sex_of_audio_group = dm.Demographic(evaluation.quiz_data["Wie viel Kontak.. "], "Wie viel Kontak.. ")
+    print(sex_of_audio_group.demographic_data.value_counts())
     #evaluation.log_eval.df.sort_values(by=["VP"], inplace=True)
-    #evaluation.log_eval.df.to_csv("evaluation_output.csv")
+    #evaluation.log_eval.df.to_csv("evaluation_output.c
 
     # This code block is used to visualize the quiz scores using a box plot.
     #colors1 = ['lightskyblue', 'darkslateblue', 'lavender', 'mediumpurple' ] #,'plum'