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import numpy as np # linear algebra | |
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) | |
import re | |
import string | |
import nltk | |
import matplotlib.pyplot as plt | |
import seaborn as sns | |
sns.set_style('darkgrid') | |
import plotly.express as ex | |
import plotly.graph_objs as go | |
import plotly.offline as pyo | |
from plotly.subplots import make_subplots | |
pyo.init_notebook_mode() | |
nltk.download('vader_lexicon') | |
from nltk.sentiment.vader import SentimentIntensityAnalyzer as SIA | |
from wordcloud import WordCloud,STOPWORDS | |
from pandas.plotting import autocorrelation_plot | |
from statsmodels.graphics.tsaplots import plot_acf | |
from statsmodels.graphics.tsaplots import plot_pacf | |
from statsmodels.tsa.seasonal import seasonal_decompose | |
from nltk.util import ngrams | |
from nltk import word_tokenize | |
from nltk.stem import PorterStemmer | |
from nltk.stem import WordNetLemmatizer | |
import random | |
plt.rc('figure',figsize=(17,13)) |
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