How to iterate over rows of .csv file and pass each row to a time-series analysis model?

Question

I want to write a program in python that iterate over each row of a data-matrix in a .csv file and then pass each row as an input to time-series-analysis model and the output(which is going to be a single value) of each row analysed over model will be stored in a form of column.

So far, I have tried iterating over rows, passing it through model and printing each output:

import pandas as pd
import numpy as np
from statsmodels.tsa.ar_model import AR
from random import random


data=pd.read_csv('EXAMPLEMATRIX.csv',header=None)
for i in data.iterrows():
    df=np.asarray(i)
    model=AR(df)
    model_fit=model.fit()
    yhat=model_fitd.predict(len(df),len(df))
    print(yhat)

but I get an error:

ValueError: maxlag should be < nobs

Please help me solve this problem or finding out where it is going wrong or provide me a reference for solving this problem.

THANKS in advance

Asked By: user12971591

||

Source

Answer 1

Use that instead:

import pandas as pd
import numpy as np
from statsmodels.tsa.ar_model import AR
from random import random

for i in range(data.shape[0]):
    row = data.iloc[i]
    model=AR(row.values)
    model_fit=model.fit()
    yhat=model_fit.predict(len(row),len(row))
    print(yhat)

Answered By: Barış Can Tayiz

How to iterate over rows of .csv file and pass each row to a time-series analysis model?

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