如何使用 pandas 将附加列表中的数据插入 csv 文件？

Question

I have a predicted data which is scraped from a website and applied ARIMA algorithm in the form below

predicted=12891.806866, expected=12890.000000
predicted=12889.863342, expected=12890.000000
predicted=12880.874762, expected=12890.000000
.....
......
........
predicted=10453.575744, expected=10999.000000
predicted=10873.639037, expected=10999.000000
predicted=11021.455329, expected=10490.000000
predicted=10620.855937, expected=10490.000000

I got this data by below snippet

for t in range(len(test)):
    model = arima_model.ARIMA(history, order=(10,1,0))
    model_fit = model.fit(disp=0)
    output = model_fit.forecast()
    yhat = output[0]
    predictions.append(yhat)
    obs = test[t]
    history.append(obs)
    print("predicted=%f, expected=%f" % (yhat, obs))
    print(predictions) #returns only single value [array([12755.95876035])]
    print(history) #returns [15095, 14890, 14890, 14449, 14449, 14449, 14890, 14890, 14890, 14890, 14890, 14890, 14890, ....................................... ,12990, 12990, 12990, 12990, 12990]

When i try to add this data to the existing column in the csv file i dont really see all the data filling in all the rows. I tried with different techniques which is know. But i failed miserably. I realized that i am not reading/copying the data in proper way to insert in the csv file. The techniques which i written below are simple examples i tried

1.
df = pd.read_csv("mydata.csv")
df['Predicted'] = yhat
df['Expected'] = obs 
df.to_csv("mydata.csv")

2.
with open("mydata.csv", "w") as data:
    w = csv.DictWriter(data, fieldnames={"Predicted", "Expected"})
    w.writeheader()
    w.writerow({'Predicted': yhat, 'Expected': obs})
    #Even w.writerows didn't really help

3.
df.insert(value=yhat, column="Predicted", allow_duplicates = True)

RESULT:
Empty DataFrame
Columns: [Expected, Predicted]
Index: []

i ended up with column filled up with only one row from the above print("predicted=%f, expected=%f" % (yhat, obs))

I want to fill mydata.csv with all predicted and expected values. I knew that i am missing some technique here. It would be great if someone helps me.

Thanks in Advance!

Answer 1

If your predictions and history are the "appended lists":

df = pd.read_csv("mydata.csv")
df['Predicted'] = predictions
df['Expected'] = history 
df.to_csv("mydata.csv")

Answer 2

I am a bit happy to answer my own question. Bringing for loop after opening the csv file 'with' worked.

with open('mydata.csv', 'a+') as csvfile:
    fieldnames = ['Expected', 'Predicted']
    w = csv.DictWriter(csvfile, fieldnames=fieldnames)
    w.writeheader()
    for t in range(len(test)):
        model = ARIMA(history, order=(10, 1, 0))
        model_fit = model.fit()
        output = model_fit.forecast()
        yhat = output[0]
        predictions.append(yhat)
        obs = test[t]
        history.append(obs)
        print("predicted=%f, expected=%f" % (yhat, obs))
        w.writerow({'Expected' : obs, 'Predicted' : yhat})

df_predicted = pd.read_csv("mydata.csv")
print(df_predicted)