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+3 votes
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in Machine Learning by (4.2k points)

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'

1 Answer

+3 votes
by (6.8k points)

Here, the syntax is provided for rolling function in pandas with version above 0.18.0.

Need to change:

moving_avg = pd.rolling_mean(ts_log,12)

to:

moving_avg = ts_log.rolling(12).mean()

Pandas Tutorial is also one of the things where one can get an invaluable insight regarding the problem.

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