# -*- coding: utf-8 -*-
"""
Created on Fri Aug 20 12:18:39 2021

@author: bharathivts
"""

import pandas as pd

df =  pd.read_csv('balanced_reviews.csv')

df.shape

df.columns

df.sample(10)

df['reviewText'][0]

df['overall'].value_counts()

df.isnull().any(axis = 0)

df.dropna(inplace =  True)

df = df [df['overall'] != 3]

import numpy as np

df['Positivity'] = np.where(df['overall'] > 3 , 1 , 0)

#NLP


b7ffc7c5f3beefd90a842c1eeb5ef541dd585487
<mask token>

<mask token>
df.shape
df.columns
df.sample(10)
df['reviewText'][0]
df['overall'].value_counts()
df.isnull().any(axis=0)
df.dropna(inplace=True)
<mask token>

<mask token>
df = pd.read_csv('balanced_reviews.csv')
df.shape
df.columns
df.sample(10)
df['reviewText'][0]
df['overall'].value_counts()
df.isnull().any(axis=0)
df.dropna(inplace=True)
df = df[df['overall'] != 3]
<mask token>
df['Positivity'] = np.where(df['overall'] > 3, 1, 0)

<mask token>
import pandas as pd
df = pd.read_csv('balanced_reviews.csv')
df.shape
df.columns
df.sample(10)
df['reviewText'][0]
df['overall'].value_counts()
df.isnull().any(axis=0)
df.dropna(inplace=True)
df = df[df['overall'] != 3]
import numpy as np
df['Positivity'] = np.where(df['overall'] > 3, 1, 0)

# -*- coding: utf-8 -*-
"""
Created on Fri Aug 20 12:18:39 2021

@author: bharathivts
"""

import pandas as pd

df =  pd.read_csv('balanced_reviews.csv')

df.shape

df.columns

df.sample(10)

df['reviewText'][0]

df['overall'].value_counts()

df.isnull().any(axis = 0)

df.dropna(inplace =  True)

df = df [df['overall'] != 3]

import numpy as np

df['Positivity'] = np.where(df['overall'] > 3 , 1 , 0)

#NLP

