[Python] How can I fix "ValueError: Expected 2D array, got 1D array instead" in scikit-learn?

I want to classify the files in my disk based on the file type by making use of a classifier. The code I have written is,

import sklearn
import numpy as np


# Importing a local data set from the desktop
import pandas as pd
mydata = pd.read_csv('file_format.csv',skipinitialspace=True)
print mydata


x_train = mydata.script
y_train = mydata.label

#print x_train
#print y_train
x_test = mydata.script

from sklearn import tree
classi = tree.DecisionTreeClassifier()

classi.fit(x_train, y_train)

predictions = classi.predict(x_test)
print predictions


And I am getting the error as,

script class div label
0 5 6 7 html
1 0 0 0 python
2 1 1 1 csv
Traceback (most recent call last):
File "newtest.py", line 21, in <module>
classi.fit(x_train, y_train)
File "/home/initiouser2/.local/lib/python2.7/site-
packages/sklearn/tree/tree.py", line 790, in fit
X_idx_sorted=X_idx_sorted)
File "/home/initiouser2/.local/lib/python2.7/site-
packages/sklearn/tree/tree.py", line 116, in fit
X = check_array(X, dtype=DTYPE, accept_sparse="csc")
File "/home/initiouser2/.local/lib/python2.7/site-
packages/sklearn/utils/validation.py", line 410, in check_array
"if it contains a single sample.".format(array))
ValueError: Expected 2D array, got 1D array instead:
array=[ 5. 0. 1.].
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.


How can I fix this problem?

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