initial commit

Prog_2A/lab_2/histogramm.py

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+import numpy as np
+
+bins = ["  0-9: ","10-19: ","20-29: ","30-39: ","40-49: ","50-59: ","60-69: ","70-79: ","80-89: ","90-99: "]
+
+def get_distribution():
+    # Generate normal distribution (mean_value, standard_deviation, size)
+    exam_points = np.random.normal(60, 20, 67)
+    # round to integer datatype
+    exam_points = np.rint(exam_points).astype(int)
+    # clip values between 15 and 95
+    exam_points = np.clip(exam_points, 15, 95)
+
+    for points in exam_points:
+        pass
+
+    return exam_points
+
+def generate_arr():
+    arr = np.ndarray((10,10), dtype=object)
+
+    for pos in range (10):
+        arr[(pos,0)] = bins[pos]
+
+    print(arr)
+
+def main():
+    generate_arr()
+
+main()