Trouble training xgboost on categorical column

I met the exactly same issue when i am doing Rossmann Sales Prediction Project. It seems like new version of xgboost do not accept the datatype of StateHoliday, Assortment, and StoreType. you can check the datatype as Mykhailo Lisovyi suggested by using

print(test_train.dtypes)

you need to replace test_train here with your X_train

you might can get

DayOfWeek                      int64
Promo                          int64
StateHoliday                   int64
SchoolHoliday                  int64
StoreType                     object
Assortment                    object
CompetitionDistance          float64
CompetitionOpenSinceMonth    float64
CompetitionOpenSinceYear     float64
Promo2                         int64
Promo2SinceWeek              float64
Promo2SinceYear              float64
Year                           int64
Month                          int64
Day                            int64

the error raised up to object type. You can convert them with

from sklearn import preprocessing
lbl = preprocessing.LabelEncoder()
test_train['StoreType'] = lbl.fit_transform(test_train['StoreType'].astype(str))
test_train['Assortment'] = lbl.fit_transform(test_train['Assortment'].astype(str))

Everything will go well after those steps.

Try this

train_store['StateHoliday'] = pd.to_numeric(train_store['StateHoliday'])
train_store['Assortment'] = pd.to_numeric(train_store['Assortment'])