adding all files done so far

random_sampling/test.py

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+import numpy as np
+import pandas as pd
+import itertools
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# np.random.seed(127)
+low = 1000
+high = 1200
+repeat = 120
+anom_perc = 0.2
+
+sns.set()
+sns.set_style("darkgrid")
+
+
+def generator(low: float, high: float, repeat: int):
+
+    for i in range(repeat):
+        num = np.random.uniform(low, high)
+        curve = float(i) ** 2
+        num = num + curve
+        if num > high * 1.2:
+            low = num - 10
+            high = num + 5
+        elif num < low:
+            low = num - 5
+            high = num + 10
+        else:
+            pass
+        yield num
+
+
+mygenerator = generator(low, high, repeat)
+
+
+df = pd.DataFrame([])
+
+for i, j in zip(mygenerator, np.arange(repeat)):
+    df = df.append([pd.DataFrame({'time': j, 'bets': i, },
+                                 index=[0])]).round(0)
+
+
+def create_anom(dataframe, number):
+    for _ in itertools.repeat(None, number):
+        rows = dataframe.shape[0]
+        anomaly = f"{float(dataframe.iloc[-1]['bets']) * (1 - anom_perc)}"
+        anomaly = float(anomaly)
+        dataframe = dataframe.append([pd.DataFrame(
+            {'time': rows, 'bets': anomaly},
+            index=[0])])
+    return dataframe
+
+
+df_anom = create_anom(df, 3)
+
+f, axes = plt.subplots(2, 1)
+
+for ax in axes:
+    ax.set_ylim([low * 0.5, high * 1.5])
+
+sns.lineplot(x='time', y='bets', data=df, ax=axes[0])
+sns.lineplot(x='time', y='bets', data=df_anom, ax=axes[1])
+plt.show()