Unable to Vectorize categorical features

Question

I have a dataset in this form:

Restaurant Name   Online_Order   Average_price    Location    Table_Booking        Rating

Pot Au Feu          Yes            65              Franklin     Available           4.2
The Aviary          No             42              Clinton      Available           4.4
Brass Tacks         Yes            29              Lebanon      Not Available       4.1

This dataset has totally 40023 rows. Also, there is no missing or Null values in any columns. 'Rating' column is the class label.

Initially I have done train test split

X = data.drop('Rating',axis=1)
y = data['Rating']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)

Then I have separated out the categorical features so that I can vectorize all of them together.

X_train_categorical_featues = X_train[['Restaurant_Name','Online_Order','Location','Table_Booking']]
X_test_categorical_featues = X_test[['Restaurant_Name','Online_Order','Location','Table_Booking']]

Now when I tried countvectorizer on them, they are giving me wrong results.

vectorizer = CountVectorizer()
vectorizer.fit(X_train_categorical_features)
X_tr_vectorized = vectorizer.transform(X_train_categorical_features)
X_test_vectorized = vectorizer.transform(X_test_categorical_features)

When I am printing X_tr_vectorized or X_test_vectorized , they are giving me a 3*3 sparse matrix which is completely wrong because I have 40023 rows in my dataset.

Can someone please suggest that what wrong I am doing ??

Answer 1

Try this...

import { map } from 'rxjs/operators';
import { Observable } from 'rxjs';

insertRecord(form: NgForm):Observable<any> {
 return this.service.postEmployee(form.value).pipe(map(((res: any[]): void=> { 

this.toastr.success('Inserted successfully', 'Employee Details'); 

this.resetForm(form); this.service.refreshList(); }), } }