Run a pickle file in python

Question

I have 3 pickle files

model.pkl
x_train.pkl
y_train.pkl

Now i want to run some coding on what if tool . When i searched i found a base code in internet but i dont know how to run that code with this pickle file. Can someone hlp me ?

pasting the sample code that i found from internet .

features=df.drop('area',axis=1)
target=df[["area"]]
X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.2)
label_encoder=preprocessing.LabelEncoder()
X_train['month']=label_encoder.fit_transform((X_train['month']))
X_train[‘day’]=label_encoder.fit_transform((X_train['day']))
X_test['month']=label_encoder.fit_transform((X_test['month']))
X_test['day']=label_encoder.fit_transform((X_test['day']))
X_train
params = {'n_estimators': 200, 'max_depth': 10,
          'learning_rate': 0.1, 'loss': 'ls','random_state':0}
reg_mod = GradientBoostingRegressor(**params)
reg_mod.fit(X_train, y_train)
def adjust_prediction(z):
 testing_data = pd.DataFrame(X_test, columns=X_test.columns.tolist())
 return reg.predict(testing_data)

from witwidget.notebook.visualization import WitConfigBuilder
from witwidget.notebook.visualization import WitWidget
num_data= 2000  
tool_height = 1000 
test_examples = np.hstack((X_test[:num_data].values,y_test[:num_data]))
config_builder = (WitConfigBuilder(test_examples.tolist(), X_test.columns.tolist() + ["area"])
  .set_custom_predict_fn(adjust_prediction)
  .set_target_feature('area')
  .set_model_type('regression'))
WitWidget(config_builder, height=tool_height)

So basically I want run widgets part and see in the pickle file that is given. Its a regression model that was build .

since I don't have the source code I don't know how to run with a pickle file . Can someone pls help>

Thanks Meera

Answer 1

import pandas as pd

model = pd.read_pickle("/yourlocation/model.pkl",compression=None)

These lines will help to unpickle the file and gives the data or information in your model pickle file.