view.py

def output(request):
    dff = pd.read_csv(r'C:\Users\Downloads\data.csv')
    y = dff['diagnosis'].values
    x = dff.drop('diagnosis', axis=1).values
    x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.40)
    model = LogisticRegression()
    model.fit(x_train, y_train)
    v1 = np.array((request.GET['n1']))

pred = model.predict([v1])
    pred1 = ""
    if pred==[1]:
        pred1 = "positive"
    else:
        pred1 = "negative"
return render(request, 'prediction.html', {"predictResult":**pred1**})

prediction.html

<div>
    <form action="output">
        <table >
            <tr>
                <td align="right">Pregnancies</td>
               <td align="left"><input type="text" name="n1"></td>
            </tr>
    </table>
     <input type="submit">
    </form>

    Result:{{ predictResult }}
</div>

How to feed 30 comma sepetared values into this code v1 = np.array((request.GET[‘n1’])) of view.py
I tried above but
** getting error mesage as below**

ValueError at /prediction/output
Expected 2D array, got 1D array instead:
array=[‘17.99,10.38,122.8,1001,0.1184,0.2776,0.3001,0.1471,0.2419,0.07871,1.095,0.9053,8.589,153.4,0.006399,0.04904,0.05373,0.01587,0.03003,0.006193,25.38,17.33,184.6,2019,0.1622,0.6656,0.7119,0.2654,0.4601,0.1189’].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.