code: import numpy as np
  import pandas as pd
  import matplotlib.pyplot as plt
  from pandas.plotting import lag_plot
  from pandas import datetime
  from statsmodels.tsa.arima_model import ARIMA
  from sklearn.metrics import mean_squared_error
  
  df = pd.read_csv("corona2.csv")
  df.head(6)
  
  plt.figure()
  lag_plot(df['InfectadosDia'], lag = 1)
  plt.title('TESLA Stock - Autocorrelation plot with lag = 1')
  plt.show()
  
  plt.plot(df["Date"], df["InfectadosDia"])
  plt.xticks(np.arange(0,200,5), df['Date'][0:200:5], rotation="vertical")
  plt.title("TESLA stock price over time")
  plt.xlabel("time")
  plt.ylabel("deaths")
  plt.show()
  
  train_data, test_data = df[0:int(len(df)*0.7)], df[int(len(df)*0.7):]
  training_data = train_data['InfectadosDia'].values
  test_data = test_data['InfectadosDia'].values
  history = [x for x in training_data]
  model_predictions = []
  N_test_observations = len(test_data)
  for time_point in range(N_test_observations):
      model = ARIMA(history, order=(4,1,0))
      model_fit = model.fit(disp=0)
      output = model_fit.forecast()
      yhat = output[0]
      model_predictions.append(yhat)
      true_test_value = test_data[time_point]
      history.append(true_test_value)
  MSE_error = mean_squared_error(test_data, model_predictions)
  print('Testing Mean Squared Error is {}'.format(MSE_error))
  
  
  test_set_range = df[int(len(df)*0.7):].index
  plt.plot(test_set_range, model_predictions, color='blue', marker='o', linestyle='dashed',label='Muertes pronosticadas python')
  plt.plot(test_set_range, test_data, color='red', label='Muertes reales')
  plt.title('Muertes covid')
  plt.xlabel('Fecha')
  plt.ylabel('Muertes')
  plt.xticks(np.arange(125,200,1), df.Date[125:200:1], rotation="vertical")
  plt.legend()
  plt.show()
  
apis: matplotlib.pyplot.legend sklearn.metrics.mean_squared_error pandas.read_csv matplotlib.pyplot.figure matplotlib.pyplot.title numpy.arange matplotlib.pyplot.show matplotlib.pyplot.ylabel pandas.plotting.lag_plot matplotlib.pyplot.plot matplotlib.pyplot.xlabel