1. Importing Library files
First of all,
import the important library files, which are used in the entire sentimental
analysis. Like NLTK, pandas, NumPy, sklearn, text blob, etc.
pandas are used for importing CSV files (used in next step), nltk is used
for natural language processing, TextBlob is built on the shoulders of
NLTK and Pattern, sklearn is used for feature extraction.
2. Importing Datasets
Before starting,
let’s read the file from the dataset in order to perform different
tasks on it. In the entire article, we will use the YouTube sentiment
dataset from the Kaggle platform.
https://www.kaggle.com/datasnaek/youtube#UScomments.csv).Here, comm is
dataframe name, pd.read_csv( ) is pandas function which is used in
import the entire dataset. UScomments.csv is file name, which is kept in
same file path. error_bad_lines=False,(here, false means bad lines will
be dropped from the DataFrame). comm.head() is use for display the
first five row of data frame.
