ciasimbaya/TimeSeries

1from datetime import datetime2import numpy as np3import pandas as pd4from sklearn.ensemble import RandomForestRegressor5import gradio as gr6import plotly.graph_objects as go7from huggingface_hub import from_pretrained_keras8import os9 10 11def predictAirPassengers(df, split):12    ts= pd.read_csv('DemandaQuito.csv')13    df2 =ts.copy()14    ttSplit=split/10015    ts['Month']=pd.to_datetime(ts['Month'])16    ts.rename(columns={'#Valor':'Valor'},inplace=True)17    ts=ts.set_index(['Month'])18    ts['months'] = [x.month for x in ts.index]19    ts['years'] = [x.year for x in ts.index]20    ts.reset_index(drop=True, inplace=True)21 22    # Split Data23    X=ts.drop("Valor",axis=1)24    Y= ts["Valor"]25    X_train=X[:int (len(Y)*ttSplit)] 26    X_test=X[int(len(Y)*ttSplit):]27    Y_train=Y[:int (len(Y)*ttSplit)] 28    Y_test=Y[int(len(Y)*ttSplit):]29 30    # fit the model31    rf = RandomForestRegressor()32    rf.fit(X_train, Y_train)33    34    df1=df2.set_index(['Month'])35    df1.rename(columns={'#Valor':'Valor'},inplace=True)36    train=df1.Valor[:int (len(ts.Valor)*ttSplit)]37    test=df1.Valor[int(len(ts.Valor)*ttSplit):]38    preds=rf.predict(X_test).astype(int) 39    predictions=pd.DataFrame(preds,columns=['Valor'])40    predictions.index=test.index41    predictions.reset_index(inplace=True)42    predictions['Month']=pd.to_datetime(predictions['Month'])43    print(predictions)44    45    #combine all into one table46    ts_df=df.copy()47    ts_df.rename(columns={'#Valor':'Valor'},inplace=True)48    train= ts_df[:int (len(ts_df)*ttSplit)]49    test= ts_df[int(len(ts_df)*ttSplit):] 50 51    df2['Month']=pd.to_datetime(df2['Month'])52    df2.rename(columns={'#Valor':'Valor'},inplace=True)53    df3= predictions54    df2['origin']='ground truth'55    df3['origin']='prediction'56    df4=pd.concat([df2, df3])57    print(df4)58    return df459 60demo = gr.Interface(61    fn =predictAirPassengers,62    inputs = [63        gr.Timeseries(label="Input for the timeseries", max_rows=1, interactive=False),64        gr.Slider(1, 100, value=75, step=1, label="Train test split percentage"),65    ],66    outputs= [67       gr.LinePlot(x='Month', y='Valor', color='origin')68       #gr.Timeseries(x='Month')69 70    ],71    examples=[72        [os.path.join(os.path.abspath(''), "DemandaQuito_dt.csv"), 75],73    ]74)75 76demo.launch()