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# import standard libraries
import numpy as np
import pandas as pd
import os
import random
from sklearn import preprocessing

os.chdir(os.path.join(os.getcwd(), "..", "..", "data", "raw"))

# read the data
df = pd.read_csv("tweet_product_company.csv", encoding = "ISO-8859-1")

# get the head
df.head(10)

# get the tail
df.tail(10)

# null count
df.isnull().sum()

# get the shape
df.shape

# get the unique emotions
np.unique(df["is_there_an_emotion_directed_at_a_brand_or_product"])

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