I am trying to build an ARIMA for anomaly detection. I need to find the moving average of the time series graph I am trying to use pandas 0.23 for this
import pandas as pd
import numpy as np
from statsmodels.tsa.stattools import adfuller
import matplotlib.pylab as plt
from matplotlib.pylab import rcParams
rcParams['figure.figsize'] = 15, 6
dateparse = lambda dates: pd.datetime.strptime(dates, '%Y-%m')
data = pd.read_csv('AirPassengers.csv', parse_dates=['Month'], index_col='Month',date_parser=dateparse)
data.index
ts = data['#Passengers']
ts.head(10)
plt.plot(ts)
ts_log = np.log(ts)
plt.plot(ts_log)
moving_avg = pd.rolling_mean(ts_log,12) # here is the error
pd.rolling_mean
plt.plot(ts_log)
plt.plot(moving_avg, color='red')
error:Traceback (most recent call last): File "C:\Program Files\Python36\lastmainprogram.py", line 74, in moving_avg = pd.rolling_mean(ts_log,12) AttributeError: module 'pandas' has no attribute 'rolling_mean'