initial commit

app.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+import gradio as gr
+from statsmodels.tsa.holtwinters import ExponentialSmoothing
+from statsmodels.tsa.arima.model import ARIMA
+from statsmodels.tsa.statespace.sarimax import SARIMAX
+
+
+def plot_graph(data, algorithm):
+    df = pd.read_csv(data)
+
+    columns = df.columns.values
+
+    if len(columns) < 2:
+        raise gr.Error('Неверная структура данных. Ожидается второй столбец value.')
+
+    df['Date'] = pd.to_datetime(df[columns[0]])
+    df = df.groupby(pd.Grouper(key='Date', freq='ME'))[columns[1]].sum().reset_index()
+    df.set_index('Date', inplace=True)
+
+    if algorithm == 'Exponential Smoothing':
+        if len(df) < 24:
+            raise gr.Error("Для Exponential Smoothing нужны данные за как минимум 24 месяца.")
+        model = ExponentialSmoothing(df[columns[1]], seasonal_periods=12, trend="add", seasonal="add")
+        model_fit = model.fit()
+    elif algorithm == 'ARIMA':
+        model = ARIMA(df[columns[1]], order=(1, 1, 1), seasonal_order=(1, 1, 1, 12))
+        model_fit = model.fit()
+    elif algorithm == 'SARIMA':
+        model = SARIMAX(df[columns[1]], order=(1, 1, 1), seasonal_order=(1, 1, 1, 12))
+        model_fit = model.fit(disp=False)
+
+    last_date = df.index[-1]
+    forecast_dates = pd.date_range(start=last_date, periods=101, freq='MS')[1:]
+    prediction = model_fit.forecast(steps=100)
+
+    plt.figure(figsize=(10, 5))
+    plt.plot(df[columns[1]], label=columns[1])
+    plt.plot(forecast_dates, prediction, label="Прогноз")
+    plt.title(f'Прогноз  {columns[1]} на следующие 100 месяцев')
+    plt.legend()
+
+    return plt
+
+
+if __name__ == "__main__":
+    iface = gr.Interface(fn=plot_graph,
+                         inputs=[gr.File(label="\'Date - Value\'. Example: 2010-01-01,100"),
+                                 gr.Radio(["Exponential Smoothing", "ARIMA", "SARIMA"],
+                                          label='Выберите алгоритм')],
+                         outputs="plot"
+                         )
+
+    iface.launch()

requirements.txt

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+gradio==4.33.0
+matplotlib==3.9.0
+pandas==2.2.2
+statsmodels==0.14.2